Multidrug resistant invasive non-typhoidal Salmonella ST313 isolated in Brazil features unique pathogenic mechanisms

doi:10.21203/rs.3.rs-2729258/v1

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Multidrug resistant invasive non-typhoidal Salmonella ST313 isolated in Brazil features unique pathogenic mechanisms

https://doi.org/10.21203/rs.3.rs-2729258/v1

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Invasive non-typhoidal Salmonella (iNTS) from the clonal type ST313 (S. Typhimurium ST313) is the major cause of invasive salmonellosis disease in Africa. Recently in Brazil, iNTS ST313 strains have been isolated from different sources, but there is a lack of understanding the mechanisms behind how these gut bacteria are able to break the gut barrier and reach the patient’s bloodstream. Herein, we compared 13 S. Typhimurium ST313 strains genomes isolated from human-blood cultures investigating aspects of virulence and resistance mechanisms. RNAseq analyses were also performed between the clinical blood isolate and SL1344 prototype, which belongs to ST19 and it was originally isolated from human feces. That analysis reveals here 15-upregulated genes related to pathogenesis in S. Typhimurium ST313 compared to SL1344 (ST19) such as sopD2, sifB, pipB, amongst others. We have also compared these clinical with non-clinical isolates from Brazil, a total of 22 genomes were studied by single nucleotide polymorphism (SNPs). The epidemiological analysis of 22 genomes of S. Typhimurium ST313 strains grouped them into three distinct clusters (A, B and C) by SNP analysis, where cluster A comprised five, the group B six, and the group C 11. The 13 clinical blood isolates were all resistant to streptomycin, 92. 3% strains were resistant to ampicillin and 15.39% strains were resistant to kanamycin. The resistance genes acrA, acrB, mdtK, emrB, emrR, mdsA and mdsB related to the production of efflux pumps were detected in all (100%) strains studied, similar to pathogenic traits investigated. In conclusion, we evidenced the S. Typhimurium ST313 strains isolated in Brazil are different of the African strains ST313. The elevated frequencies of virulence genes such as sseJ, sopD2 and pipB are a major concern in these Brazilian isolates, showing a higher pathogenic potential.

Salmonella Typhimurium ST313

Phylogeny

Virulence and resistance genes

Galleria mellonella

RNA-seq

Salmonella enterica serovar Typhimurium is common case of gastroenteritis worldwide (Haraga et al., 2008; Ashton et al., 2017). The Centers for Disease Control and Prevention (CDC) estimates that Salmonella causes approximately 1.2 million illnesses and 450 deaths every year only in the United States (CDC, 2021). The sequence type (ST) 19 is the most studied and prevalent ST amongst the S. Typhimurium strains, followed by the ST34 and ST313 (Achtman et al., 2012; Almeida et al., 2017). Recently, the S. Typhimurium ST313 strains were described in sub-Saharan Africa associated with antimicrobial resistance and high mortality, with very high prevalence in the African continent (Feasey et al., 2014; Ley et al., 2014).

Whole genome sequence (WGS) has become an useful tool in the last decade for molecular detailed characterization (Shivani et al., 2015; Tang et al., 2019). Different phylogenetic approaches can be applied using sequencing data, such as the construction of phylogenetic trees from single copy marker genes and from single nucleotide polymorphism (SNPs), whole genome multilocus sequence typing (wgMLST), as well as the comparison and analysis of orthologous protein clusters (OrthoVenn) and confirmation of the sequence type (ST) through multilocus sequence typing (MLST) (Wang et al., 2015; Alikhan et al., 2018; Wu, 2018; Seribelli et al., 2021a).

Groups at highest risk for severe salmonellosis include people with weakened immune systems, adults older than 65 years, children younger than 5 and under cancer treatment (CDC, 2021). Salmonella may cause severe diarrhea, hospitalization and even death in these groups. Another worldwide concern has been the increase in the number of Salmonella strains multidrug resistant strains to different classes of antibiotics. Antibiotic resistance may be closely associated with the development of bloodstream infection and/or treatment failure (CDC, 2021). The current perspectives for iNTS can be alarming, because its worldwide distribution have grown mainly in people with comorbidities, including HIV and malaria in Africa, since there are many multidrug-resistant strains being isolated in this continent (Haselbeck et al., 2017).

S. Typhimurium ST313 strains are iNTS generally isolated from human blood and considered more invasive for their ability to evade the gastrointestinal tract and achieve the bloodstream (Singletary et al., 2016). More recently in Brazil our group has isolated S. Typhimurium ST313 strains from foods, human feces and blood (Almeida et al., 2017; Perez-Sepulveda et al., 2021).

The pathogenesis of S. Typhimurium is a complex multifactorial and orchestrated mechanism to cause gastroenteritis (Haraga et al., 2008). Several pathogenicity islands have been described in the literature and were better elucidated with the sequencing of S. Typhimurium LT2 and SL1344 strains, including islands that classically are associated to infectious processes, such as Salmonella Pathogenicity Islands 1 and 2 (SPI-1 and SPI-2). These islands are required for invasion and survival of this pathogen in epithelial and phagocytic cells and systemic infection in mice (Galan & Curtiss, 1989; Ochman et al., 1996; Cirillo et al., 1998; Hensel et al., 1998; Moreira et al., 2010). Moreover, SPI-1 and SPI-2 encode distinct Type III Secretion System (T3SS), molecular needle-like structures responsible for injecting essential effector proteins during these two distinct extra and intracellular moments of infection (Galan & Curtiss, 1989; Groisman & Ochman, 1993; Shea et al., 1996; Hensel et al., 1998; Moreira et al., 2010).

Only few Salmonella serovars harbor specific virulence plasmids. In the case of S. Typhimurium, a major virulence plasmid has approximately 95 Kb and it is denominated as pSLT. Specifically, in this plasmid there is a highly conserved genomic region denominated spv (Salmonella plasmid virulence), which encodes for four structural SpvA, SpvB, SpvC and SpvD proteins and the SpvR regulator (Fàbrega & Vila, 2013). In addition, the SpvB and SpvC effectors are encoded within the SPI-2, participating in the replication within SCV, macrophage apoptosis, and host decreasing inflammatory response (Brown et al., 1986; Gulig & Doyle 1993; Lobato-Márquez et al., 2016; Hiley et al., 2019).

Recent studies employed RNAseq analyses to elucidate possible transcriptional differences between S. Typhimurium ST313 and ST19 strains. Recently, a collaborative work performed by this research group showed that S. Typhimurium ST313 isolated from human feces established better colonization and invasion in the murine colon and higher expression of genes related to pathogenesis in comparison to S. Typhimurium ST19 prototype strain SL1344 (Seribelli et al., 2021b).

An alternative manner to assess the pathogenicity of these pathotypes is using an alternative infection model, Galleria mellonella, was employed since they have a primitive innate immune response with a certain degree of homology with the mammalian systems, the hemocytes present in the hemolymph behave similarly to phagocytic cells showing robust oxidative burst in response to microbial targets (Marmaras & Lampropoulou, 2009; Bender et al., 2013; Viegas et al., 2013). Furthermore, in contrast to other invertebrate models, experiments with G. mellonella worms can be performed at 37ºC, to mimic the human pathogens (Bender et al., 2013). Studies with fungi and several microbial pathogens, including S. Typhimurium, demonstrated a positive correlation in the data obtained in virulence assays using mouse model compared to the findings in G. mellonella model (Brennan et al., 2002; Slater et al., 2011; Seribelli et al., 2020).

It is important to emphasize that there is a lack of studies conducted with S. Typhimurium ST313 strains isolated in Brazil that performed genomic analyzes, gene expression assays and in vivo tests which emphasizes the importance of the information to be obtained using these assays. The aims of this work were (i) to compare S. Typhimurium ST313 strains isolated from clinical and non-clinical sources in Brazil using phylogenetic trees, protein orthologous clusters analysis, virulence, resistance genes, (ii) to perform RNAseq of the S. Typhimurium ST313 isolated from blood in Brazil and S. Typhimurium SL1344 (ST19) strains in vitro, and (iii) to assess the virulence of the strains via the G. mellonella infection model.

2.1. Bacterial strains

The 13 S. Typhimurium ST313 strains isolated from human blood in the São Paulo State in Brazil, between 1998 and 2011 were selected from the collection of the UNESP Hospital (Table 1), all in accordance with relevant guidelines and regulations of UNESP, as previously reported (Perez-Sepulveda et al., 2021). Another 9 S. Typhimurium ST313 genomes isolated from humans and food in the São Paulo State in Brazil previously sequenced and described to in silico only analysis (Almeida et al., 2017) were included here for comparative genomic analyzes including wgMLST and SNPs tree. The reference strain S. Typhimurium SL1344 prototype (ST19) was originally isolated from the intestine of a calf with salmonellosis and has been considered a model pathogen and S. Typhimurium ST313 African lineage 2 reference strain D23580 (Kingsley et al., 2009).

Table 1

Identification and year of isolation of the 24 S. Typhimurium genomes ST313 used in the study.
GenBank Accession Number		Year of isolation	Reference or source
014250355.1	78/98 Human Blood	1998	Perez-Sepulveda et al., 2021
014250355.1	220/98 Human Blood	1998	Perez-Sepulveda et al., 2021
014250355.1	522/98 Human Blood	1998	Perez-Sepulveda et al., 2021
014250355.1	2366/98 Human Blood	1998	Perez-Sepulveda et al., 2021
014250355.1	31217/04 Human Blood	2004	Perez-Sepulveda et al., 2021
014250355.1	32714/04 Human Blood	2004	Perez-Sepulveda et al., 2021
014250355.1	339/07 Human Blood	2007	Perez-Sepulveda et al., 2021
014250355.1	1880/08 Human Blood	2008	Perez-Sepulveda et al., 2021
014250355.1	2081/08 Human Blood	2008	Perez-Sepulveda et al., 2021
014250355.1	3956/10 Human Blood	2010	Perez-Sepulveda et al., 2021
014250355.1	4270/10 Human Blood	2010	Perez-Sepulveda et al., 2021
014250355.1	5339/10 Human Blood	2010	Perez-Sepulveda et al., 2021
014250355.1	1435/11 Human Blood	2011	Perez-Sepulveda et al., 2021
LVGE00000000	CFSAN033876 Human Faeces	1989	Almeida et al.2017
LVGD00000000	CFSAN033877 Human Faeces	1990	Almeida et al.2017
LVGA00000000	CFSAN033881 Human Faeces	1993	Almeida et al.2017
LVFZ00000000	CFSAN033882 Human Faeces	1995	Almeida et al.2017
LVFX00000000	CFSAN033884 Raw pork sausage	1996	Almeida et al.2017
LUJB00000000	CFSAN033886 Human Faeces	1998	Almeida et al.2017
LUJA00000000	CFSAN033887 Lettuce	1998	Almeida et al.2017
LVFU00000000	CFSAN033891 Human Faeces	2000	Almeida et al.2017
LUIX00000000	CFSAN033894 Human Faeces	2003	Almeida et al.2017
000210855.2	SL1344 ASM21085v2 Cattle ST19 UK	-	-
000027025.1	D23580 ASM2702v1 Human Blood ST313	2004	Kingsley et al. 2009

2.2. Antimicrobial resistance profile of S. Typhimurium ST313 strains

The antimicrobial susceptibility test was performed by the Disk Diffusion Method (DDM) for 11 antimicrobials, including ampicillin, streptomycin, chloramphenicol, gentamicin, kanamicina, tetracycline, nalidixic acid, sulfonamides, trimethoprim-sulphamethaxazole, ciprofloxacin and colistin following the all recommendations of the Clinical and Laboratory Standard Institute (CLSI, 2022). The Escherichia coli ATCC 25922 strain was used as a control.

2.3. Virulence plasmids and resistance genes

The virulence plasmid genes were identified for all 13 S. Typhimurium isolates ST313 from blood using the Virulence Factors Database (VFDB) (http://www.mgc.ac.cn/VFs/main.htm) with a threshold of ≥ 70% identity and ≥ 70% coverage comparing plasmid S. enterica subsp. enterica serovar Typhimurium str. LT2 pSLT, 93939 bp, NC_003277 (Chen et al., 2005).

The presence of plasmids was determined in silico using Plasmid Finder (Center for Genomic Epidemiology, https://cge.cbs.dtu.dk/services/PlasmidFinder/) with a threshold set for a minimum of 95% identity, and minimum coverage of 60% (Carattoli et al., 2014). BLASTn (https://blast.ncbi.nlm.nih.gov/Blast.cgi) was used to confirm the location, percentages of identity, and coverage between the S. enterica subsp. enterica serovar Typhimurium str. LT2 pSLT, 93939 bp, NC_003277 reference sequences of the pSLT, pBT1, pBT2 and pBT3 plasmids, and the spvABCDR, pefABCD, rck and mig-5 genes of the positive and negative genomes for IncFIIs.

The resistance genes were detected using ResFinder 4.1 - Center for Genomic Epidemiology (https://cge.cbs.dtu.dk/services/ResFinder/) with settings of threshold of 90%, and minimum length of 60% and Comprehensive Antibiotic Resistance Database (CARD) with high quality/coverage (includes contigs > 20,000 bp and excludes prediction of partial genes) that is available at https://card.mcmaster.ca/analyze/rgi (Camacho et al., 2009; McArthur et al., 2013; Bortolaia et al., 2020; Zankari et al., 2020).

2.4. RNA-seq

S. Typhimurium ST313 522/98 was isolated from human blood in 1998 at UNESP Hospital and SL1344 (ST19), all in accordance with relevant guidelines and regulations of UNESP, as previously reported (Perez-Sepulveda et al., 2021). The strains were cultured for 16–18 hours in LB broth (Difco) at 37°C. The cultures were diluted into LB broth (Difco) and incubated under shaking at 37°C for 3h until reaching an optical density of 1.0 at 600 nm (Seribelli et al., 2021b). In order to disrupt cells and inactivate nucleases, it was used 500 µL of TRIzol (Life Technologies) and RNA was isolated using the RNA RiboPure® Bacteria kit (Thermo Fisher Scientific), according to the manufacturer’s instructions. The concentration and purity of the total RNA were verified by NanoDrop 2000 Spectrophotometer (Thermo Scientific) at 260nm and 280 nm (Seribelli et al., 2021b). Extracted with A260 nm/A280 nm ratio between 2.0 and 2.2 were considered adequate, in the same way, were used for quantification and verification of samples quality the Bioanalyzer RNA 6000 Nano (Agilent Technologies) and Bioanalyzer DNA 1000 kits (Agilent Technologies) (Seribelli et al., 2021b). The ribosomal RNA was depleted by kit QIAseq FAST Select (Qiagen®) and were converted into cDNA libraries using the TruSeq® Stranded mRNA kit (Illumina). After preparing the library, it was quantified by QIAseq Library Quant System (Qiagen®), using the standard curve method to perform the sequencing with the MiSeq® v3 kit (Illumina). The sequencing was performed using MiSeq® sequencer (Illumina) and the biological triplicate were prepared according to the manufacturer’s instructions (Illumina).

2.5. Mapping of RNA-seq libraries and differential gene expression analysis

Initially raw reads served as input for Trimmomatic (Bolger et al., 2014), which performed quality filtering removing Illumina adapters sequences, low quality bases (phred score quality > 20) and reads shorter than 35 bp. Trimming was followed by read error correction by SGA k-mer-based algorithm (Simpson & Durbin, 2012). The pre-processed reads were compared to the raw reads through FastQC analysis (Andrews, 2010) to evaluate the trimming and quality control performed previously.

Next the reads were mapped against the Salmonella enterica serovar Typhimurium SL1344 reference genome (Kroger et al., 2012) Genbank access code GCA_000210855.2, using Bowtie2 software (Langmead & Salzberg, 2012) following previously described optimization (Baruzzo et al., 2017).

The gene differential expression calling was achieved initially by counting the number of reads in each transcript through HTSeq (Anders et al., 2015). Finally, the count data were direct to differential analysis with DESeq2 R package (Love et al., 2014).

2.6. Galleria mellonella infection model

The purpose of this study was to investigate the virulence between S. Typhimurium ST313 and S. Typhimurium SL1344 (ST19) that were grown overnight, harvested by centrifugation and resuspended in 1000 µL PBS. The experiments were performed and adapted as described by Scalforo et al. (2017).

The susceptibility of G. mellonella to bacterial infection was used in this study. Groups of 10 larvae weighing ∼200–250 mg were used for all experiments and were inoculated with 10⁸, 10⁶ and 10⁴S. Typhimurium CFU/larva by injections of 10 µL of bacterial suspension using Hamilton micro syringe into the hemocoel through the last left pro-leg. As controls, PBS injected animals were included in each experiment. After infection, larvae were placed in sterile petri plates, incubated in the dark at 37^◦C and the number of dead larvae was counted and recorded daily for three days. All experiments were performed in triplicate, and only the experiments where the larvae survived up to 3dpi (days post infection) were included in the analysis.

2.7. Whole genome sequencing

Whole genome sequencing of 13 Typhimurium ST313 strains isolated from human blood in Brazil were performed on the HiSeq 4000 (Illumina) at University of Liverpool, as part of the 10K Salmonella Genome Consortium deposited in Enterobase (https://enterobase.warwick.ac.uk/species/index/senterica) (Perez-Sepulveda et al., 2021). The S. Typhimurium ST313 genomes were assembled as previously described (Seribelli et al., 2021c; Silva et al., 2021). Briefly, raw reads were processed by a5 pipeline (August 2016 version) (Coil et al., 2015), starting with trimming with Trimmomatic (Bolger et al., 2014), performing quality filtering removing adaptor sequences, low quality bases (phred score quality < 28), and short reads (> 35 bp). The read error correction was performed by SGA (Simpson & Durbin, 2012) following IDBA-UD algorithm (Peng et al., 2012) for de novo assembling succeeded by SSPACE (Boetzer et al., 2011) scaffolding. Next it was executed reference-assisted scaffolding through MeDuSa 1.6 (Bosi et al., 2015) using the deposited genomes of close-related S. Typhimurium strains LT2, SL1344, ST4-74, 14028S and D23580 to guide the scaffolds in the correct order and orientation, building a single scaffold. The final scaffolds were passed through up to 20 iterations in Gapfiller 1.10 (Nadalin et al., 2012), which used the error-corrected reads to fulfill the gaps between the contigs sequences, improving L₅₀contig count.

2.8. Phylogeny

The genomes of all the 22 S. Typhimurium ST313 strains described in item 2.1 were used in the phylogenetic analyzes.

Whole genome multilocus sequence typing (wgMLST) was performed using the module Build_PGAdb formed by four steps including contigs for building DB, annotation: Prokka, allele extraction and pan-genome allele DB. The wgMLST tree was constructed using the Build_wgMLSTtree module in three steps allelic sequence generating, clustering and genetic relatedness tree. We used as input files the genomes contigs in the Fasta format. The parameters used for PGAdb-builder were alignment coverage and identity ≥ 90% (Liu et al., 2016).

The phylogenetic tree based on SNPs of the whole genome sequencing was performed by CSI Phylogeny 1.4 (Call SNPs & Infer Phylogeny) of the Center for Genomic Epidemiology at https://cge.cbs.dtu.dk/services/CSIPhylogeny/ - following the parameters: select min. dep that SNP positions 10x, select min. relative dep that SNP positions 10%, select minimum distance between SNPs (prune) 10 bp, select min. SNP quality 30, select min. read mapping quality 25 and select min. Z-score 1.96 (Kaas et al., 2014). The SNPs matrix included was a maximum of 818 SNPs among all S. Typhimurium ST313 strains studied.

2.9. Orthologous protein clusters analysis

The characterization of the orthologous proteins was performed by OrthoVenn2 (Xu et al., 2019) available at https://orthovenn2.bioinfotoolkits.net/home in order to determine unique biological processes present in the S. Typhimurium ST313 strains based on comparison among SNPs tree groups denominated A, B and C.

2.10. Statistical analysis

All statistical analyzes were performed using the GraphPad Prism v7.04 (GraphPad Software, San Diego, CA) by one-way analysis of variance (ANOVA) and Dunnett's multiple comparisons post-test. Data were considered significant when p < 0.05. Graphical and statistical analyzes of the virulence assay in Galleria mellonella were performed by the Long-rank method (Mantel-Cox).

3.1. Antimicrobial resistance profile of S. Typhimurium ST313 blood-isolated strains

All 13/13 (100%) blood-isolated S. Typhimurium ST313 strains were resistant to streptomycin, 12/13 (92. 3%) strains were resistant to ampicillin and 2/13 (15.39%) strains were resistant to kanamycin (Table 2). All the strains were susceptible to other antibiotics assayed such as chloramphenicol, gentamicin, tetracycline, nalidixic acid, sulfonamides, sulfamethoxazole-trimethoprim, ciprofloxacin and colistin. The resistance genes acrA, acrB, mdtK, emrB, emrR, mdsA and mdsB related to the production of efflux pumps were detected in all (100%) S. Typhimurium ST313 strains with identity for all genes between 91.6–100% (Table 2). Nevertheless, the strains have not shown resistance to antimicrobial related to these genes. Resistance genes related to enzyme production were also investigated but were not detected in any of these S. Typhimurium ST313 strains.

Table 2

Genotypic and phenotypic antimicrobial resistance profiles of the 13 S. Typhimurium ST313 strains studied isolated from bloodstream.
Barcode	Identification	Efflux Pump Resistance genes (Identity%)	Phenotypic Resistance profiles
FD01848810	78/98	acrA, acrB, mdtK, emrB, emrR, mdsA, mdsB (91.69–100%)	SM
FD01848812	220/98	acrA, acrB, mdtK, emrB, emrR, mdsA, mdsB (91.69–100%)	SM-AMP
FD01848813	522/98	acrA, acrB, mdtK, emrB, emrR, mdsA, mdsB (91.69–100%)	SM-AMP-KAN
FD01848818	2366/98	acrA, acrB, mdtK, emrB, emrR, mdsA, mdsB (91.69–100%)	SM-AMP
FD01848828	31217/04	acrA, acrB, mdtK, emrB, emrR, mdsA, mdsB (91.69–100%)	SM-AMP
FD01848833	32714/04	acrA, acrB, mdtK, emrB, emrR, mdsA, mdsB (91.69–100%)	SM-AMP
FD01848836	339/07	acrA, acrB, mdtK, emrB, emrR, mdsA, mdsB (91.69–100%)	SM- AMP
FD01848843	1880/08	acrA, acrB, mdtK, emrB, emrR, mdsA, mdsB (91.69–100%)	SM-KAN
FD01848844	2081/08	acrA, acrB, mdtK, emrB, emrR, mdsA, mdsB (91.69–100%)	SM-AMP
FD01848852	3956/10	acrA, acrB, mdtK, emrB, emrR, mdsA, mdsB (91.69–100%)	SM-AMP
FD01848853	4270/10	acrA, acrB, mdtK, emrB, emrR, mdsA, mdsB (91.69–100%)	SM-AMP
FD01848858	5339/10	acrA, acrB, mdtK, emrB, emrR, mdsA, mdsB (91.69–100%)	SM-AMP
FD01848859	1435/11	acrA, acrB, mdtK, emrB, emrR, mdsA, mdsB (91.69–100%)	SM-AMP
SM- streptomycin; AMP- ampicillin and KAN- kanamycin.

3.2. Virulence genes were detected in sequenced isolates

The spvABCDR operon, pefABCD operon, rck and mig-5 genes were detected in 12/13 S. Typhimurium ST313 isolates from human blood. In order to confirm the location of genes, Plasmid Finder was used to document the presence of the IncFIIs plasmid incompatibility group, which belongs to the pSLT plasmid. Specifically, BLASTn analysis for all isolates confirmed the presence of the pSLT plasmid carrying these regions in the 12 isolates with coverage of 100% and 99–100% of identity (Table 3). The pBT1, pBT2 and pBT3 plasmids were not detected in any of the S. Typhimurium ST313 genomes studied.

Table 3

Characteristics of the plasmid genes of 13 *Salmonella* Typhimurium isolates from human blood that presented these genes by Virulence factors database (VFDB).
Genes	Proportion of isolates	Query cover (%)	Identity (%)
spvA	12/13	100	100
spvB	12/13	100	100
spvC	12/13	100	100
spvD	12/13	100	99–100
spvR	12/13	100	100
pefA	12/13	100	100
pefB	12/13	100	100
pefC	12/13	100	99–100
pefD	12/13	100	100
rck	12/13	100	100
mig-5	12/13	100	100
IncFIIs and pSLT were confirmed in these genomes.

3.3. Virulence traits differently expressed in ST313 blood-isolate transcript

Interestingly, transcriptome studies were performed between the S. Typhimurium ST313 and SL1344 (ST19) strains revealed 399 genes were differentially expressed (168 upregulated and 231 downregulated). S. Typhimurium ST313 showed upregulated genes linked to various biological processes including ethanolamine, primary alcohol, and amine metabolism, also pathogenesis. Conversely, the downregulated genes expression were mainly linked to cellular general processes, metabolism, transport, biological adhesion, and response to stimulus (Fig. 1). Specifically, 15 SPI-2 encoded genes were upregulated in ST313 when compared to SL1344 (ST19) strain, directly linked in S. Typhimurium invasion, such as sopD2, sifB, pipB, ssaB, ssaI, ssaG, ssaJ, ssaM, ssaR, ssaT, ssaK, sseJ, spvC, spvA and srcA. SPI-2 effector proteins and regulators are essential for intracellular survival and replication (Srikanth et al., 2011). The higher levels of gene expression for the SPI-2-encoded effectors sopD2 (3.6-fold), sifB (2.9-fold) and pipB (2.1-fold) are related to Salmonella inducing filaments (Sifs) formation, an important structure to intracellular fitness and replication. The ssaB gene was more than 5.2-fold increased, the SsaB is required for SPI-2 chaperone protein SpiC for the injectosome. Moreover, the ssaJ gene was more than 3.2-fold increased, which it is required for T3SS- effector function, and the sseJ gene was 2.0-fold upregulated, another key effector in the T3SS SPI-2-encoded (Fig. 2).

Furthermore, it was observed that spvA (3.0-fold) and spvC (3,3-fold) genes were upregulated in the Salmonella virulence plasmid. In addition, an increase of 3.8-fold for katE gene, which encodes for a catalase, important to protect the bacteria from the oxidative stress. As illustrated by the volcano plot for these pathogenesis-related traits in the S. Typhimurium ST313 (Fig. 2).

3.4. S. Typhimurium ST313 blood-isolates infectivity in Galleria mellonella model

Infectious diseases in vivo models are essential to evaluate pathogens. Herein, we employed the survival within Galleria mellonella model to better compare virulence of distinct clinical strains during three days post infection. We assessed distinct concentrations of 10⁸, 10⁶ and 10⁴ CFU/ larva inoculated with S. Typhimurium ST313 compared to SL1344 (ST19) were tested. At 10⁸ CFU/larva concentration, all larvae inoculated with SL1344 (ST19) (100%) and 90% with ST313 deceased after 1 dpi. On the other hand, the 10⁶ CFU/larva concentration has shown 30% survival on the 1dpi with SL1344 (ST19) and 40% for ST313, on the 2nd and 3rd day survival remained at 20% for inoculation SL1344 (ST19) and 30% for ST313 (Fig. 3). However, the percentage of survival was 100% during the 3 dpi in the larvae inoculated with the concentration of 10⁴ CFU/larva inoculated withSL1344 (ST19) or ST313 (data not shown). Infection by S. Typhimurium caused higher melanization at concentrations above 10⁶ CFU/larva and the results demonstrated that mortality was dose-dependent. In addition, data shown are representative of three independent experiments which obtained similar results.

3.5. Phylogenetic comparisons between these geographical distinct Brazilian and African-ST313 isolates

The wgMLST employed here was able to separate the S. Typhimurium SL1344 (ST19) reference genome (GCF000210855) from the other 23 S. Typhimurium ST313 genomes isolated from blood, feces and food in Brazil, and the D23580 ST313 strain in Supplementary Fig. 1 (Fig. S1).

The phylogenetic analysis based on SNPs grouped the 24 S. Typhimurium genomes isolated in Brazil into three groups denominated A, B and C. Specifically, cluster A comprised five S. Typhimurium ST313 genomes, including four isolated from blood and only one isolated from human feces. Group B comprised six S. Typhimurium ST313 genomes isolated from blood. Group C comprised 13 S. Typhimurium ST313 genomes, and they were subdivided into C1 and C2. Group C1 grouped four S. Typhimurium ST313 genomes isolated from blood and group C2 comprised nine S. Typhimurium ST313 genomes isolated from human feces, food and the two reference strains, SL1344 from ST19 and D23580 from African ST313 (Fig. 4).

3.6. Orthologous ST313-isolates analysis delivers 3 distinct evolutive groups

The orthologous protein clusters analysis was performed with the 22 strains and 2 prototype genomes to compare homologous protein-based on the groups found in the phylogenetic tree on SNPs denominated cluster A, B and C (Fig. 4). Specifically, the comparisons indicated the orthologous protein clusters presented in the genomes of the S. Typhimurium strains studied, evidencing that these proteins were important and remained throughout the biological speciation events for these S. Typhimurium. The orthologous protein clusters found in all genomes are involved in metabolic and pathogenesis processes showed in detail in Supplementary Table 1.

Emergent pathogens surveillance in public health should be a constant concern. In Brazil, few studies have been conducted on Salmonella Typhimurium ST313 an important intestinal pathogen recently associated with more serious invasive infections. Together the results of the present study of S. Typhimurium ST313 isolates from the bloodstream in the period between 1998–2011 corroborate with the other ST313 isolated from different sources between 1989–2003 in Brazil.

Herein, 13 clinical S. Typhimurium ST313 strains from human blood-isolated cultures in Brazil were evaluated and fully characterized, including antimicrobial resistance profiles, virulence plasmid, transcriptome analysis, in vivo infection, and phylogenetic diversity compared to other 9 distinct S. Typhimurium ST313 isolates from clinical and non-clinical sources.

All 13 S. Typhimurium ST313 strains isolated from patients at the University Hospital in Brazil were resistant to streptomycin. Streptomycin is not often used to treat infections caused by Salmonella enterica; however, it has been previously used as a growth promoter in avian production, an important concerning factor due to the possibility of resistance transmission amongst bacterial strains via food and zoonotic contact (McDermott et al., 2016; Almeida et al., 2018).

The ampicillin resistance was found in 12 (92.3%) S. Typhimurium ST313 strains and two (15.4%) were also resistant to kanamycin. Antimicrobial resistance of S. Typhimurium strains in the United States has increased in recent decades, Wang and colleagues used CDC and National Antimicrobial Resistance Monitoring System (NARMS) data from 1996 to 2016 from human, animal, and retail meats isolates to demonstrate the increased resistance profile to ampicillin, streptomycin, sulfonamides, and tetracycline for this serovar (Wang et al., 2019).

The multidrug resistance observed for S. Typhimurium ST313 strains in the African continent has been a serious public health problem, being responsible for a high mortality rate of 20.6% in patients infected with this iNTS (Uche et al., 2017; Canals et al., 2019). In contrast, Almeida et al. (2018) observed low antimicrobial resistance in S. Typhimurium ST313 isolated from different sources such as food, feces and human blood in Brazil. Increasing drug resistance in foodborne pathogens is an alarming concern, specially nontyphoidal Salmonella in the last 13 years in US (CDC, 2019).

The resistance genes related to the production of efflux pumps were detected in the S. Typhimurium studied. Efflux pumps are organized in structures covering the width of the Gram-negative cell envelope and selectively communicates the cytoplasm with the external environment. The AcrAB-TolC system has been one of the most studied, transporting a wide range of substrates and conferring resistance to several antibiotics including some β-lactams, (Munita & Arias, 2016). In addition, Buckley et al. (2006) shown in S. Typhimurium SL1344, the AcrAB-TolC system may also exert the ability to efflux toxic compounds from the lysosome, aiding in intracellular survival. It has been observed in mutants of the system that have had reduced adhesion and/or invasion abilities (Buckley et al., 2006).

Moreover, all 13 S. Typhimurium ST313 genomes were investigated by Center for Genomic Epidemiology and CARD, on their resistance genes database. None resistance gene related to the production of beta-lactamases were found in any analyzes performed, which is in agreement with the phenotypic disc diffusion tests (data not shown), once the S. Typhimurium ST313 strains were resistant to few antibiotics. These analyzes are essential to know more about the epidemiology of this important ST in Brazil.

The S. Typhimurium virulence plasmid (pSLT) was detected in 92.3% of the strains confirming the pathogenic potential of the strains studied and their differences when compared to other ST313 strains isolated in other locations as previously described (Pulford et al., 2021). Furthermore, the spv operon has been associated with the survival and multiplication of Salmonella spp. in host macrophages (Rychlik et al., 2006). On the other hand, the pef fimbrial operon (plasmid encoded fimbriae) is important for the adhesion of Salmonella spp. to the small intestine in infant mouse resulting in accumulation of fluid in the lumen (Baumler & Heffron, 1995; Ledeboer et al., 2006). The rck and mig-5 plasmid genes have been associated with the resistance of S. Typhimurium to the host complement system and the neutralization of toxic compounds produced by macrophages, respectively (Rychlik et al., 2006).

Recently, a genomic study with the D23580 S. Typhimurium ST313 strain isolated in Malawi showed pSLT lack and the presence of the pSLT-BT plasmid carrying the Tn21-like locus, associated with resistance to different antibiotics including chloramphenicol, ampicillin, kanamycin, streptomycin, sulfonamides and trimethoprim (Kingsley et al., 2009; Singletary et al., 2016). The pSLT plasmid was also direct linked with S. Typhimurium ST313 strains isolated from humans and food in Brazil, with the presence of the spvABCDR locus, pefABCD locus, rck, and mig-5 genes in all isolates (Seribelli et al., 2020). Pulford and collaborators (2021) have studied phylogenetic clades of S. Typhimurium ST313 genomes isolated from distinct locations and their relationship with different plasmids. Our analyses here show the Brazilian S. Typhimurium ST313 strains are genetically similar to the UK isolates, where it was found the presence of pSLT and the absence of pBT1, pBT2 and pBT3 in comparison to ST313 L1, L2 and L3 strains isolated from Africa (Pulford et al., 2021).

Herein, the S. Typhimurium ST313 strains expression were upregulated for the ssa (secretion system apparatus) genes when compared to SL1344 levels, such as ssaB, ssaI, ssaG, ssaJ, ssaM, ssaR and ssaT, responsible to encode the T3SS structural component of SPI-2 (Hensel et al., 1997). In general, the majority of the upregulated genes were related to the pathogenesis of this important pathogen present mainly via SPI-1 and SPI- 2-encoded effectors during S. Typhimurium infection (Shea et al., 1999; Heijden & Finlay, 2012). The SPI-2 effectors are essential to internalized S. Typhimurium and required for the Salmonella-containing vacuole (SCV) maturation (Ruiz-Albert et al., 2002; Freeman et al., 2003). Here, the upregulated SPI-2 encoded-genes were evident, such as the sseJ gene, an acyltransferase/lipase that is associated in SCV biogenesis in human epithelial cells (Ruiz-Albert et al., 2002; Freeman et al., 2003). Some studies suggested that the protein SseJ is necessary for full virulence of S. Typhimurium in mice and for proliferation into human cells culture (Ohlson et al., 2005; Trombert et al., 2010). The increased expression of the sseJ gene in S. Typhimurium ST313 compared to SL1344 (ST19) was verified in this study.

Our data corroborate with a recent study, which observed that the sopD2 and pipB genes were upregulated in S. Typhimurium ST313 isolated from human feces after transcriptomic analysis compared to S. Typhimurium SL1344 (ST19) (Seribelli et al., 2021b). Altogether, the data indicated that ST313 was more efficient in colonizing and invading the large intestine of C57BL/6J mice due to its increased expression of the sopD2, pipB hilA and ssaS genes, which are found or effectors of SPI-1 and SPI-2 (Seribelli et al., 2021b). Similarly, here we demonstrated that sopD2 and pipB were also upregulated in the ST313 isolates from human blood when compared to SL1344 (ST19), that shows that pathogenesis of these isolates are a major concern. Conversely, previously characterized African-isolated iNTS ST313 strains invaded non-phagocytic cells less efficiently and stimulated less inflammasome activation than ST19 isolates associated with gastroenteritis (Carden et al., 2015).

Interestingly, study showed that decreased KatE catalase activity in S. Typhimurium ST313 L1, L2 and L3 isolates compared to SL1344 (ST19) this phenotype may be associated with adaptation to a restricted host range and loss of characteristics related to environmental persistence (Singletary et al., 2016). The KatE catalase protects S. Typhimurium from oxidative stress environments and has shown maximum activity in stationary phase cultures (Pulford et al., 2021). Here, we observed increased expression of katE in S. Typhimurium ST313 in comparison with SL1344(ST19).

In vivo studies such as the G. mellonella are important alternative model to evaluate virulence of distinct pathogenic microorganisms (Ramarao et al., 2012). The model consists in G. mellonella larvae that are easily cultivated in large numbers and at low cost and produce human-like components of the innate immune response (Scorzoniet al., 2015). Herein, we found that mortality rates in the infected larvae with S. Typhimurium SL1433 and ST313 at concentrations of 10⁸, 10⁶ and 10⁴ CFU/larva were similar after three days of incubation. The concentration of 10⁶ CFU/larva had a survival rate on the 2nd and 3rd dpi remaining at 20% for SL1344 (ST19) and 30% for ST313. Recently, Bender and colleagues observed 100% mortality of larvae in less than 10 hours after inoculation of 10⁷ CFU/larva with S. Typhimurium NCTC 12023 (Bender et al., 2013). Moreover, according to Viegas et al. (2013), the concentration of 10⁸ CFU/larva of S. Typhimurium resulted in 100% of larval mortality in G. mellonella on the 1st day after infection and it was also observed that using concentrations lower than 10⁵ CFU/larva, the mortality was almost null or close from zero.

The phylogenetic comparison tree based on SNPs grouped better the S. Typhimurium ST313 genomes in comparison to wgMLST, showing that ST313-isolated strains from human blood in Brazil are genetically distinct from most strains isolated from human feces and food in this country and from S. Typhimurium ST19 and ST313 reference genomes (Fig. 1). Furthermore, the orthologous protein clusters analysis demonstrated that orthologous genes involved in metabolism and pathogenesis have been preserved in these S. Typhimurium strains ST313 isolated from human blood in Brazil (Supplementary Table 1).

The transcriptomic analyzes and further characterization showed that S. Typhimurium ST313 strains isolated from human blood, human feces and foods in Brazil are quite different from the ST313 strains isolated from human blood in Africa, including differences in phylogeny, antimicrobial resistance and virulence plasmids. The pathogenic potential was evidenced in the S. Typhimurium ST313 strains studied due to presence or higher expression of crucial virulence genes related to invasion and survival in host cells. Our work here contributed for a better understanding of these invasive strains and their diversity, which present a serious emergent public health problem.

Ethics approval and consent to participate: Not applicable (All previous published bacterial strains)

Consent for publication: Not applicable

Availability of data and material: The data from 22 S. Typhimurium genomes released under the BioProjects, PRJNA656707 and PRJNA186035, available in (https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA656707) (https://www.ncbi.nlm.nih.gov/bioproject/186035).

Competing interests: The authors declare no conflict of interest

Funding: São Paulo Research Foundation (FAPESP) (Proc. 2019/19338-8, 2019/03049-7, 2019/26696-8, and 2022/05030-4) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) — Brasil Finance Code 001 for financial support. During this work, Seribelli, A.A. was supported by a scholarship from São Paulo Research Foundation (FAPESP) (Proc. 2017/06633-6). Falcão, J. P. received a productive fellowship from Council for Scientific and Technological Development (CNPq) Grant 304399/2018-3.

Authors contributions: I.M.M. performed and wrote the article; A.A.S. performed and wrote the article; T.R.M.R performed specific experiments; P.S. performed analysis; B.C.L. performed specific experiments; R.T.H. technical contribution; J.P.F. supervision, revision, and funding; C.G.M. designing, supervision, revision, and funding.

Acknowledgements: All financial Support

Achtman M, Wain J, Weill FX, et al. Multi locus sequence typing as a replacement for serotyping in Salmonella enterica. PLoS Pathog. 2012;8:e1002776. https://doi.org/10.1371/journal.ppat.1002776.
Alikhan NF, Zhou Z, Sergeant MJ, et al. A genomic overview of the population structure of Salmonella. PLoS Genet. 2018;14:e1007261. https://doi.org/10.1371/journal.pgen.1007261.
Almeida F, Seribelli AA, Silva P, et al. Multi locus sequence typing of Salmonella Typhimurium reveals the presence of the highly invasive ST313 in Brazil. Infect Genet Evol. 2017;51:41–4. https://doi.org/10.1016/j.meegid.2017.03.009.
Almeida F, Seribelli AA, Medeiros MIC, et al. Phylogenetic and antimicrobial resistance gene analysis of Salmonella Typhimurium strains isolated in Brazil by whole genome sequencing. PLoS ONE. 2018;13:e0201882. https://doi.org/10.1371/journal.pone.0201882.
Anders S, Pyl PT, Huber W. HTSeq—a Python frame-work to work with high-throughput sequencing data. Bioinformatics. 2015;31:166–9. 10.1093/bioinformática/btu638.
Andrews S. 2010. FastQC: A quality control tool for high through-put sequence data. http://www.bioinformatics.babraham.ac.uk/rojects/fastqc/.
Baruzzo G, Hayer KE, Kim EJ, et al. Simulation-based comprehensive bench-marking of RNA-seq aligners. Nat Methods. 2017;14:135–9. 10.1038/nmeth.4106.
Ashton PM, Owen SV, Kaindama L, et al. Public health surveillance in the UK revolutionises our understanding of the invasive Salmonella Typhimurium epidemic in Africa. Genome Med. 2017;9:1–13. 10.1186/s13073-017-0480-7.
Baumler AJ, Heffron F. Identification and sequence analysis of lpfABCDE, a putative fimbrial operon of Salmonella typhimurium. J Bacteriol. 1995;177:2087–97. 10.1128/jb.177.8.2087-2097.
Bender JK, Wille T, Blank K, et al. LPS Structure and PhoQ activity are important for Salmonella Typhimurium virulence in the Galleria mellonella infection model. PLoS ONE. 2013;8:e73287. 10.1371/journal.pone.0073287.
Boetzer M, Henkel CV, Jansen HJ, et al. Scaffolding pre-assembled contigs using SSPACE. Bioinformatics. 2011;27:578–9. https://doi.org/10.1093/bioinformatics/btq683.
Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20. 10.1093/bioinformática/btu170.
Bosi E, Donati B, Galardini M, et al. MeDuSa: a multi-draft based scaffolder. Bioinformatics. 2015;31:2443–51. https://doi.org/10.1093/bioinformatics/btv171.
Brennan M, Thomas DY, Whiteway M, et al. Correlation between virulence of Candida albicans mutants in mice and Galleria mellonella larvae. FEMS Immunol Med Microbiol. 2002;34:153–7. 10.1111/j.1574-695X.2002.tb00617.x.
Brown DJ, Munro DS, Platt DJ. Recognition of the cryptic plasmid, pSLT, by restriction fingerprinting and a study of its incidence in Scottish Salmonella isolates. J Hyg Camb. 1986;97:193–7. 10.1017/s0022172400065268.
Canals R, Hammarlöf DL, Kröger C, et al. Adding function to the genome of African Salmonella Typhimurium ST313 strain D23580. PLoS Biol. 2019;17:e3000059. https://doi.org/10.1371/journal.pbio.3000059.
Buckley AM, Webber MA, Cooles S, et al. The AcrAB–TolC efflux system of Salmonella enterica serovar Typhimurium plays a role in pathogenesis. Cell Microbiol. 2006;8:847–56. https://doi.org/10.1111/j.1462-5822.2005.00671.x.
Carden S, Okoro C, Gordon D, et al. Non-Typhoidal Salmonella Typhimurium ST313 isolates that cause bacteremia in humans stimulate less inflammasome activation than ST19 isolates associated with gastroenteritis. Pathog Dis 73. 2015. 10.1093/femspd/ftu023.
Centers for Disease Control and Prevention (CDC). Salmonella. 2021 [Cited 2022 Aug 25]. Available from:https://www.cdc.gov/salmonella/index.html.
Cirillo DM, Valdivia RH, Monack DM, et al. Macrophage-dependent induction of the Salmonella pathogenicity island 2 type III secretion system and its role in intracellular survival. Mol Microbiol. 1998;30:175–88. https://doi.org/10.1046/j.1365-2958.1998.01048.x.
CLSI. M100-ED32:2022 Performance Standards for Antimicrobial Susceptibility Testing, 32nd Edition; 2022.
Coil D, Jospin G, Darling AE. A5-miseq: an updated pipeline to assemble microbial genomes from Illumina MiSeq data. Bioinformatics. 2015;31:587–9. https://doi.org/10.1093/bioinformatics/btu661.
Fàbrega A, Vila J. Salmonella enterica serovar Typhimurium skills to succeed in the host: virulence and regulation. Clin Microbiol Ver. 2013;26:308–41. 10.1128/CMR.00066-12.
Feasey NA, Cain AK, Msefula CL, et al. Drug resistance in Salmonella enterica ser. Typhimurium bloodstream infection, Malawi. Emerg Infect Dis. 2014;20:1957–9. 10.3201/eid2011.141175.
Freeman JA, Ohl ME, Miller SI. The Salmonella enterica serovar typhimurium translocated effectors SseJ and SifB are targeted to the Salmonella-containing vacuole. Infect Immun. 2003;71:418–27. 10.1128/IAI.71.1.418-427.2003.
Galan JE, Curtiss R 3rd. Cloning and molecular characterization of genes whose products allow Salmonella typhimurium to penetrate tissue culture cells. Proc Natl Acad Sci U S A. 1989;86:6383–7. https://doi.org/10.1073/pnas.86.16.6383.
Gulig PA, Doyle TJ. The Salmonella typhimurium virulence plasmid increases the growth rate of salmonellae in mice. Infect Immun. 1993;61:504–11.
Groisman EA, Ochman H. Cognate gene clusters govern invasion of host epithelial cells by Salmonella typhimurium and Shigella flexneri. EMBOJ. 1993;12:3779–87. 10.1002/j.1460-2075.1993.tb06056.x.
Haraga A, Ohlson MB, Miller SI. Salmonellae interplay with host cells. Nat Rev Microbiol. 2008;6:53–66. 10.1038/nrmicro1788.
Haselbeck AH, Panzner U, Im J, et al. Current perspectives on invasive nontyphoidal Salmonella disease. Curr Opin Infect Dis. 2017;30:498–503. 10.1097/QCO.0000000000000398.
Heijden J, Finlay BB. Type III effector-mediated processes in Salmonella infection. Future Microbiol. 2012;7:685–703. 10.2217/fmb.12.49.
Hensel M, Shea JE, Raupac B et al. 1997. Functional analysis of ssaJ and the ssaK/U operon, 13 genes encoding components of the type III secretion apparatus of Salmonella Pathogenicity Island 2. Mol Microbiol. 24, 155–167. doi:https://doi.org/10.1046/j.1365-2958.1997.3271699.x.
Hensel M, Shea JE, Waterman SR, et al. Genes encoding putative effector proteins of the type III secretion system of Salmonella pathogenicity island 2 are required for bacterial virulence and proliferation in macrophages. Mol Microbiol. 1998;30:163–74. https://doi.org/10.1046/j.1365-2958.1998.01047.x.
Hiley L, Graham RMA, Jennison AV. Genetic characterisation of variants of the virulence plasmid, pSLT, in Salmonella enterica serovar Typhimurium provides evidence of a variety of evolutionary directions consistent with vertical rather than horizontal transmission. PLoS ONE. 2019;14:e0215207. https://doi.org/10.1371/journal.pone.0215207.
Kingsley RA, Msefula CL, Thomson NR, et al. Epidemic multiple drug resistant Salmonella Typhimurium causing invasive disease in sub-Saharan Africa have a distinct genotype. Genome Res. 2009;19:2279–87. 10.1101/gr.091017.109.
Kröger C, Dillon SC, Cameron ADS et al. 2012. The transcriptional landscape and small RNAs of Salmonella enterica serovar Typhimurium. Proc. Natl. Acad. Sci. USA. 109, E1277-E1286. doi: 10.1073/pnas.1201061109.
Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357–9. 10.1038/nmeth.1923.
Ledeboer NA, Frye JG, McClelland M, et al. Salmonella enterica serovar Typhimurium requires the Lpf, Pef, and Tafi fimbriae for biofilm formation on HEp-2 tissue culture cells and chicken intestinal epithelium. Infect Immun. 2006;74:3156–69. 10.1128/IAI.01428-05.
Ley B, Hello SLe, Lunguya O, et al. Invasive Salmonella enterica serotype typhimurium infections, Democratic Republic of the Congo, 2007–2011. Emerg Infect Dis. 2014;20:701–4. 10.3201/eid2004.131488.
Lobato-Márquez D, Molina-García L, Moreno-Córdoba I, et al. Stabilization of the virulence plasmid pSLT of Salmonella Typhimurium by three maintenance systems and its evaluation by using a new stability test. Frente Mol Biosci. 2016;3:1–11. https://doi.org/10.3389/fmolb.2016.00066.
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550doi. 10.1186/s13059-014-0550-8.
Marmaras VJ, Lampropoulou M. Regulators and signalling in insect haemocyte immunity. Cell Signal. 2009;21:186–95. 10.1016/j.cellsig.2008.08.014.
Moreira CG, Weinshenker D, Sperandio V. QseC mediates Salmonella enterica serovar typhimurium virulence in vitro and in vivo. Infect Immun. 2010;78:914–26. 10.1128/IAI.01038-09.
Munita JM, ARIAS CA. Mechanisms of antibiotic resistance. Microbiol Spectr. 2016;4:1–37. 10.1128/microbiolspec.
Nadalin F, Vezzi F, Policriti A. 2012. GapFiller: a de novo assembly approach to fill the gap within paired reads. BMC Bioinformatics. 13 Suppl 14, S8. doi: https://doi.org/10.1186/1471-2105-13-S14-S8.
Ochman H, Soncini FC, Solomon F, et al. Identification of a pathogenicity island required for Salmonella survival in host cells. Proc Natl Acad Sci USA. 1996;93:7800–4. 10.1073/pnas.93.15.7800.
Ohlson MB, Fluhr K, Birmingham CL, et al. SseJ deacylase activity by Salmonella enterica serovar Typhimurium promotes virulence in mice. Infect Immun. 2005;73:6249–59. 10.1128/IAI.73.10.6249-6259.2005.
Peng Y, Leung HC, Yiu SM, et al. Bioinformatics. 2012;28:1420–8. https://doi.org/10.1093/bioinformatics/bts174. IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth.
Perez-Sepulveda BM, Heavens D, Pulford CV, et al. An accessible, eficiente and global approach for the large-scale sequencing of bacterial genomes. Genome Biol. 2021;22:1–18. https://doi.org/10.1186/s13059-021-02536-3.
Pulford CV, Perez-Sepulveda BM, Canals R, et al. Stepwise evolution of Salmonella Typhimurium ST313 causing bloodstream infection in Africa. Nat Microbiol. 2021;6:327–38. https://doi.org/10.1038/s41564-020-00836-1.
Ramarao N, Nielsen-Leroux C, Lereclus D. The insect Galleria mellonella as a powerful infection model to investigate bacterial pathogenesis. J Vis Exp. 2012;70:e4392. 10.3791/4392.
Rychlik I, Gregorova D, Hradecka H. Distribution and function of plasmids in Salmonella enterica. Vet Microbiol. 2006;112:1–10. https://doi.org/10.1016/j.vetmic.2005.10.030.
Ruiz-Albert J, Yu XJ, Beuzon CR, et al. Complementary activities of SseJ and SifA regulate dynamics of the Salmonella typhimurium vacuolar membrane. Mol Microbiol. 2002;44:645–61. 10.1046/j.1365-2958.2002.02912.x.
Seribelli AA, Cruz MF, Vilela FP, et al. Phenotypic and genotypic characterization of Salmonella Typhimurium isolates from humans and foods in Brazil. PLoS ONE. 2020;15:e0237886. https://doi.org/10.1371/journal.pone.0237886.
Seribelli AA, Ribeiro TRM, Silva P, Martins IM, et al. Typhimurium ST313 isolated in Brazil revealed to be more invasive and inflammatory in murine colon compared to ST19 strains. J Microbiol. 2021b;59:861–70. 10.1007/s12275-021-1082-z.
Seribelli AA, Silva P, Cruz MF, et al. Insights about the epidemiology of. Typhimurium isolates from diferent sources in Brazil using comparative genomics Gut Pathog. 2021a;13:1–15. 10.1186/s13099-021-00423-7.
Seribelli AA, Silva P, Frazão MR, et al. Phylogenetic relationship and genomic characterization of. Typhimurium strains isolated from swine in Brazil Infect Genet Evol. 2021c;93:1–12. https://doi.org/10.1016/j.meegid.2021.104977.
Silva P, Lustri BC, Castilho IG, et al. Genome profiling of fluoroquinolone-resistant uropathogenic Escherichia coli isolates from Brazil. Braz J Microbiol. 2021;52:1067–75. 10.1007/s42770-021-00513-3.
Simpson JT, Durbin R. Efficient de novo assembly of large genomes using compressed data structures. Genome Res. 2012;22:549–56. 10.1101/gr.126953.111.
Singletary LA, Karlinsey JE, Libby SJ et al. 2016. Loss of multicellular behavior in epidemic African nontyphoidal Salmonella enterica serovar Typhimurium ST313 strain D23580. MBio. 7,1–11. doi: 10.1128/mBio.02265-15.
Scalfaro C, Iacobino A, Nardis C, et al. Galleria mellonella as an in vivo model for assessing the protective activity of probiotics against gastrointestinal bacterial pathogens. FEMS Microbiol Lett. 2017;364:1–6. 10.1093/femsle/fnx064.
Shea JE, Beuzon CR, Gleeson C, et al. Influence of the Salmonella Typhimurium pathogenicity island 2 type III secretion system on bacterial growth in the mouse. Infect Immun. 1999;69:213–9. 10.1128/IAI.67.1.213-219.1999.
Shea JE, Hensel M, Gleeson C, et al. Identification of a virulence locus encoding a second type III system in Salmonella Typhimurium. Proc Natl Acad Sci U S A. 1996;93:2593–7. 10.1073/pnas.93.6.2593.
Shivani C, Abha K, Alka G et al. 2015. Comparative genome analysis of three pathogenic strains of E. coli, Salmonella and Shigella. IJSRR.4, 68–80.
Slater JL, Gregson L, Denning DW, et al. Pathogenicity of Aspergillus fumigatus mutants assessed in Galleria mellonella matches that in mice. Med Mycol. 2011;49(Suppl 1):107–13. 10.3109/13693786.2010.523852.
Srikanth CV, Mercado-Lubo R, Hallstrom K, McCormick BA. Salmonella effector proteins and host-cell responses. Cell Mol Life Sci. 2011;68:3687–97. https://doi.org/10.1007/s00018-011-0841-0.
Tang S, Orsi RH, Luo H, et al. Assessment and comparison of molecular subtyping and characterization methods for Salmonella. Front Microbiol. 2019;10:1591. 10.3389/fmicb.2019.01591.
Trombert AN, Berrocal L, Fuentes JA et al. 2010. S. Typhimurium sseJ gene decreases the S. Typhi cytotoxicity toward cultured epithelial cells. BMC Microbiol. 10, 312. doi: 10.1186/1471-2180-10-312.
Uche IV, Maclennan CA, Saul AA. Systematic review of the incidence, risk factors and case fatality rates of invasive nontyphoidal Salmonella (iNTS) disease in Africa (1966 to 2014). PLoS Negl Trop Dis. 2017;11:e0005118. 10.1371/journal.pntd.0005118.
Viegas SC, Mil-Homens D, Fialho AM, et al. The virulence of Salmonella enterica serovar Typhimurium in the insect model Galleria mellonella is impaired by mutations in RNase E and RNase III. Appl Environ Microbiol. 2013;79:6124–33. https://doi.org/10.1128/AEM.02044-13.
Wang X, Biswas S, Paudyal N, PAN, H., et al. Antibiotic resistance in Salmonella Typhimurium isolates recovered from the food chain through national antimicrobial resistance monitoring system between 1996 and 2016. Front Microbiol. 2019;10:985. 10.3389/fmicb.2019.00985.
Wang Y, Coleman-Derr D, Chen G, et al. OrthoVenn: a web server for genome wide comparison and annotation of orthologous clusters across multiple species. Nucleic Acids Res. 2015;43:78–84. https://doi.org/10.1093/nar/gkv487.
Wu YW. ezTree: an automated pipeline for identifying phylogenetic marker genes and inferring evolutionary relationships among uncultivated prokaryotic draft genomes. BMC Genom. 2018;19(Suppl 1):921. https://doi.org/10.1186/s12864-017-4327-9.
Yang J, Barrila J, Roland KL, et al. Characterization of the invasive, multidrug resistant non-typhoidal Salmonella strain D23580 in a murine model of infection. PLoS Negl Trop Dis. 2015;9:e0003839. https://doi.org/10.1371/journal.pntd.0003839.

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Multidrug resistant invasive non-typhoidal Salmonella ST313 isolated in Brazil features unique pathogenic mechanisms

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Abstract

Figures

1. Introduction

2. Materials And Methods

2.1. Bacterial strains

2.2. Antimicrobial resistance profile of S. Typhimurium ST313 strains

2.3. Virulence plasmids and resistance genes

2.4. RNA-seq

2.5. Mapping of RNA-seq libraries and differential gene expression analysis

2.6. Galleria mellonella infection model

2.7. Whole genome sequencing

2.8. Phylogeny

2.9. Orthologous protein clusters analysis

2.10. Statistical analysis

3. Results

3.1. Antimicrobial resistance profile of S. Typhimurium ST313 blood-isolated strains

3.2. Virulence genes were detected in sequenced isolates

3.3. Virulence traits differently expressed in ST313 blood-isolate transcript

3.4. S. Typhimurium ST313 blood-isolates infectivity in Galleria mellonella model

3.5. Phylogenetic comparisons between these geographical distinct Brazilian and African-ST313 isolates

3.6. Orthologous ST313-isolates analysis delivers 3 distinct evolutive groups

4. Discussion

5. Conclusions

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1