Genomic comparison of diverse Salmonella serovars isolated from swine.

Food animals act as a reservoir for many foodborne pathogens. Salmonella enterica is one of the leading pathogens that cause food borne illness in a broad host range including animals and humans. They can also be associated with a single host species or a subset of hosts, due to genetic factors associated with colonization and infection. Adult swine are often asymptomatic carriers of a broad range of Salmonella servoars and can act as an important reservoir of infections for humans. In order to understand the genetic variations among different Salmonella serovars, Whole Genome Sequences (WGS) of fourteen Salmonella serovars from swine products were analyzed. More than 75% of the genes were part of the core genome in each isolate and the higher fraction of gene assign to different functional categories in dispensable genes indicated that these genes acquired for better adaptability and diversity. High concordance (97%) was detected between phenotypically confirmed antibiotic resistances and identified antibiotic resistance genes from WGS. The resistance determinants were mainly located on mobile genetic elements (MGE) on plasmids or integrated into the chromosome. Most of known and putative virulence genes were part of the core genome, but a small fraction were detected on MGE. Predicted integrated phage were highly diverse and many harbored virulence, metal resistance, or antibiotic resistance genes. CRISPR (Clustered regularly interspaced short palindromic repeats) patterns revealed the common ancestry or infection history among Salmonella serovars. Overall genomic analysis revealed a great deal of diversity among Salmonella serovars due to acquired genes that enable them to thrive and survive during infection.

Introduction

Salmonella enterica subsp. enterica has the ability to infect a wide range of hosts, including both animals and humans. In the latter group, the bacterium causes foodborne illnesses ranging from mild diarrhea and gastroenteritis to severe systemic infections such as enteric fever [1], second only to norovirus as the causative agent of foodborne illness; Salmonella infections in humans are the leading cause of hospitalization and deaths from foodborne illness in the United States [2]. The Centers for Disease Control and Prevention has estimated 1.2 million foodborne illnesses with 19,000 hospitalizations and approximately 380 deaths in the United States annually (https://www.cdc.gov/salmonella/index.html). S. enterica ranks as the leading cause of foodborne disease as measured by the combined cost of illness and quality-adjusted life-year [3]. The direct economic losses owing to salmonellosis in the US exceed an estimated $3.5 billion per year. More than 2,600 Salmonella serovars has been confirmed by the agglutination properties of the somatic O, flagellar H, and capsular Vi antigens [4].

Inappropriate use of antimicrobials in food animal production during treatment and prevention of diseases and for growth promotion contribute to resistance, including acquisition of antibiotic resistance (AR) genes through horizontal gene transfer (HGT). Multi drug resistant (MDR) bacteria are recognized as a major threat to public health [5] and require a comprehensive approach to combat them [6]. Resistance determinants are often present on mobile genetic elements (MGE), such as plasmids, integrons etc. and can be transferred among multiple bacterial genera [7, 8]. A wide range of plasmids that carry AR and virulence genes have been reported in Salmonella [9-11]. Here we catalog all the antibiotic resistance genes and their organization in a diverse set of Salmonella from swine.

Phage play a profound role in bacterial evolution as they assist in transfer of antibiotic resistance (AR) and, virulence genes, including inserting their genome into the host’s DNA [12]. These lysogens can also become lytic by replicating and then killing their temporary host bacteria. A large number of phage have been reported from Salmonella, such as Fels-1, Gifsy-2, P22, FelixO1, etc., and some of them carry several virulence and resistance gene cassettes [5, 13–16]. Here, we investigate phage distribution among Salmonella serovars to determine the resistance and virulence genes associated with phage. Here we also characterize the CRISPR (clustered regularly interspaced short palindromic repeats) elements, which act as an adaptive immune system against exogenous DNA [17], including phage DNA. In addition, analysis of CRISPR sequences improve the discriminatory power of molecular characterization of Salmonella [18].

Few studies have been conducted to identify genetic factors associated with Salmonella serovars isolated from swine using WGS [19, 20]. In order to understand the genetic variations among different Salmonella serovars, the WGS of fourteen Salmonella serovars isolated from swine and swine swab were analyzed. The WGS data was assessed for resistance and virulence determinants, and their association with MGE was predicted. WGS was further analyzed to identify CRISPR elements and phage associated resistance and virulence genes.

Material and methods

Isolate selection and antimicrobial susceptibility testing

Fourteen Salmonella isolates were collected by the National Antimicrobial Resistance Monitoring System (NARMS) in year 2004–2005. All isolates were streaked onto Mueller-Hinton (MH) agar (Oxoid, Cambridge, UK). A single colony was selected and subsequently inoculated in MH broth (Oxoid, Cambridge, UK), and incubated for 16–18 h at 37°C with shaking (250 rpm). All isolates were subjected to susceptibility testing via the SensititreTM semi-automated antimicrobial susceptibility system (TREK Diagnostic Systems, Inc.) using a custom-made panel including amikacin, gentamicin, kanamycin, streptomycin, ampicillin, amoxicillin-clavulanic acid, ceftiofur, ceftriaxone, cefoxitin, sulfamethoxazole/sulfisoxazole, trimethoprim-sulfamethoxazole, chloramphenicol, ciprofloxacin, nalidixic acid, and tetracycline [21]. The isolates were subjected to preliminary biochemical screening to distinguish the different serogroups using serogroup-specific antisera (Difco Laboratories, Detroit, MI) and serotyping was used to identify serovars at the National Veterinary Services Laboratories, APHIS, USDA (Ames, IA).

Genome sequencing and analysis

Genomic DNA was isolated using GenElute bacterial genomic DNA kit (Sigma-Aldrich, St. Louis, MO) according to manufacturer's protocols. The quality of DNA was tested using Nanodrop and quantified using an Invitrogen Qubit 2.0 Fluorometer (Life Technologies, Carlsbad, CA). The extracted DNA was stored in 1X TE buffer (pH 8.0) at -20°C until further use. Paired-end sequencing was performed on an Illumina HiSeq2500 (Illumina Inc., San Diego, CA) as described elsewhere [22] and the reads were deposited in the SRA database under the bioproject PRJNA254816. The SRA accession numbers is available in Table 1. The reads were retrieved from the SRA dataset and reads with a phred score ≥30 were de novo assembled using the A5-pipeline_version_20141120 [23]. The genome and plasmid contigs from the assembly were sorted on the basis of remote blast using an in-house python script. The genomic contigs were annotated using PROKKA [24]. In order to reconstruct the pan-genome the assembled genomes were annotated with Prokka and used as input for Roary with the identity cut-off of 95% [25]. Roary generated clusters of homologous gene groups from which core, accessory and unique genes were predicted. The Clusters of Orthologous Groups of proteins (COGs) database was used for the functional annotation [26]. The amino acid sequences generated from the Prokka was used as input for functional annotation based on orthologous group using WebMGA online server (http://weizhong-lab.ucsd.edu/metagenomic-analysis/server/cog/). The assembled contigs and deduced amino acid sequences from Prokka were used to predict the acquired antibiotic and metal resistance genes using the ARG-ANNOT [27] and BacMet [28] respectively, with e-value (1e -10), coverage ≥90% and identity ≥90%. The adherence-associated gene cluster were identified using the Virulence Factor Database (VFDB) [29] using a threshold of ≥95% identity and ≥95% coverage. Lysogenic phage were predicted using the web-based tool PHASTER [30]. CRISPR regions were predicted using CRISPR finder [31] and blastn was done to identify similar phage among Salmonella serovars and linear comparison of similar phage was done using Easyfig [32]. The Integrall integron database (http://integrall.bio.ua.pt) was used to analyze and assign integron sequences [33]. Genes associated with plasmid replicon were identified using PlasmidFinder to identify the target sequence in the genomes of each isolate [34].

Table 1

Assembly statistics of the Salmonella enterica serovars isolated from swine and their products.

Salmonella serovar	Strain	Year	Genome					No of CDS	SRA_ID
			Length (b)	No of Contigs	Coverage(x)	GC (%)	N50
Agona	CRJJGF_0019	2005	4933904	101	78	52.1	162691	4,680	SRX791372
Anatum	CRJJGF_0121	2004	4707212	65	76	52.1	156274	4,414	SRX791374
Bovismorbificans	CRJJGF_0070	2004	4662088	89	93	52.1	168471	4,354	SRX791423
Choleraesuis	CRJJGF_0148	2004	4708469	99	80	52.1	149708	4,528	SRX791500
Cubana	CRJJGF_0088	2004	4929533	78	58	52.1	155115	4,604	SRX791441
Give	CRJJGF_0073	2004	4613042	61	89	52.1	226100	4,308	SRX791426
Heidelberg	CRJJGF_0002	2004	4853670	123	92	52.1	158927	4,558	SRX791355
Infantis	CRJJGF_0031	2005	4650782	75	76	52.1	157448	4,351	SRX791384
Minnesota	CRJJGF_0078	2004	4651740	87	95	52.1	372885	4,352	SRX791431
Manhattan	CRJJGF_0112	2005	4668352	201	90	52.1	260620	4,361	SRX791465
Ohio	CRJJGF_0161	2005	4854746	91	74	52.1	216733	4,532	SRX791512
Tennessee	CRJJGF_0089	2004	4772495	92	53	52.1	164659	4,462	SRX791442
Typhimurium	CRJJGF_0051	2004	4939221	130	69	52.1	172339	4,667	SRX791404
Worthington	CRJJGF_0141	2004	4848597	97	75	52.1	210218	4,559	SRX791493

Results

This study was the part of retrospective study to maximize the understanding of the AR gene distribution, MGE and genome diversity of the Salmonella [22] from food animals. Fourteen Salmonella isolates from swine were selected based on differences in phenotypic AR profile, serotype from the collection of NARMS isolates between 2004 and 2005.

General features and sequenced genomes

The genome statistics are presented in Table 1. In brief, the average number of contigs per genome was 95 (range: 61 to 201 contigs). The median assembly coverage ranged between 53 to 95 fold which was adequate to produce bacterial draft genomes [35]. The average GC content of each genome was 52.1% which was consistent with that of the complete S. enterica chromosome [36]. The average number of coding sequences (CDSs) per isolate was 4,480 and the highest and lowest number of CDS was obtained for S. Agona (4,680) and S. Give (4,308), respectively. Additionally, average nucleotide identity matrix showed >98% identity among the serovars and >99.9% identity to their respective reference genome sequences from NCBI Gen-Bank. The high average nucleotide identity (ANI) [37] values of pair wise genome comparisons again confirmed that these serovars were nearly identical to their corresponding reference serovars. The reads were deposited in the GenBank Sequence Read Archive (SRA) database and details are provided in Table 1.

Antimicrobial resistance genes, integrons, and plasmids

Antibiotic susceptibility assays were performed according to Clinical and Laboratory Standards Institute (CLSI) standards. Eleven isolates were resistant to at least one of the tested antibiotics and nine of them were multidrug resistant (MDR; resistant to two or more antimicrobials); the remaining three Salmonella serovars Give, Infantis, and Manhattan were susceptible to all tested antimicrobials. None of the isolates were resistant to azithromycin, ciprofloxacin or nalidixic acid. The susceptibility testing results and corresponding predicted AR genes results are summarized in Table 2. High frequency of resistance to tetracycline (9/14, 64.3%) was observed among the isolates, followed by resistance to beta-lactams (7/14, 50.0%), aminoglycosides (7/14, 50.0%) and sulfonamides (7/14, 50.0%). Three isolates 3/14, 21%). (S. Agona, S. Ohio and S. Typhimurium) were resistant to two antibiotics (chloramphenicol and sulfamethoxazole) while two isolates (2/14, 14.3%); S. Anatum and S. Worthington) were only resistant to tetracycline. The correlation between phenotypically confirmed AR and in silico predicted AR genes of the serovars is presented in Table 2. Resistance determinants were predicted with ARG-ANNOT. Hits with > 90% identity and 100% coverage were considered as positive resistance determinants. A total of 73 AR genes (59 in Table 1 and 14 aac6-I variants) were predicted from the genome sequences and at least one AR gene was predicted in each isolate (Table 1). The aminoglycoside resistance gene variants Y and aa of aac6-I was detected in all the isolates and these cryptic variants were the only aminoglycoside resistance gene variants predicted in Salmonella serovars Give, Infantis, and Mannhattan exhibited no phenotypic resistance. Among eight streptomycin resistant isolates strA and strB were detected in five isolates while four isolates carry aadA gene variants and all these three genes (strA, strB, and aadA) were detected in S. Heidelberg. Seven isolates were resistant to beta-lactams and three genes encoding beta-lactamases were identified in these seven isolates, with the most common being blaTEM-1 ((3/14), 21.4%) and blaCMY-2 ((3/14), 21.4%), followed by blaCARB-2 ((2/14), 14.3%). The Amber class A β-lactamase gene (bla) conferring resistance to ampicillin were detected in serovar Tennessee and Typhimurium. Amber classA potential ESBL (extended spectrum of beta-lactamase) gene (bla) conferring resistance to ampicillin was detected in serovars Bovismorbificans, Heidelberg and Ohio. Amber class C genes (blaCMY-2) that conferred resistance to ampicillin, amoxicillin, and ceftiofur were detected in serovars Agona, Minnesota and Ohio. Four different tetracycline resistance gene allele’s tetA, tetB, tetC and tetG were identified in the analyzed Salmonella serovars. With tetA and tetB the most frequently detected tetracycline resistances, occurring in 4/14, 28.6% and 3/14, 21.4% of isolates, respectively, followed by tetC and tetG each in 1/14, 7.1% of isolates. The macrolide resistance gene ereA was detected in Tennessee, while trimethoprim gene variants (dfrA1, A7, A12, and A16) were detected in serovars Ohio, Agona, Heidelberg, and Tennessee respectively. The sulfonamide resistance gene alleles were identified in seven Salmonella serovars; only sul1 was detected in serovar Bovismorbificans, Choleraesuis, Cubana and Typhimurium ((4/14); 28.6%), while sul1 and sul2 were detected in serovar Agona and Ohio ((2/14); 14.3%) and sul3 was detected in serovar Heidelberg ((1/14); 7.1%). The floR gene was detected in three of fourteen chloramphenicol resistant isolates and only these three serovars Agona, Ohio, and Typhimurium conferred resistance to chloramphenicol. No mutations in chromosomal genes gyrA, gyrB, parE: conferring resistance to ciprofloxacin and nalidixic acid and rRNA genes 23S rRNA, rplD, rplVb conferring resistance to macrolide were observed; a point mutation in parC at position T57S was observed in most of the studied serovars except Bovismorbificans and Typhimurium; however, none of these isolates were resistant to nalidixic acid (S2 Table).

Table 2

Antibiotic resistance phenotype and predicted antibiotic resistance and virulence genes in different Salmonella serovars.

Salmonella serovar	Virulence Gene		AGly	Bla	Tet	Sul	Chl	Others	Replicons
Agona	lpfA/B/C/D/E; avrA, slrP, sspH2, sseK1	G*	aph3”-Ia, strA, strB	blaCMY-2	tet(A)	sul1, sul2	flo(R)	dfrA7/fosA	incA/C2
		P**	STR	AMP, AUG, AXO, FOX, TIO, COT	TET	FIS	CHL	--
Anatum	avrA, slrP, sspH2	G	--	--	tet(C)	--	--	--	colE10
		P	--	--	TET	--
Bovismorbificans	lpfA/B/C/D/E, avrA, ratB, slrP, sspH2, sodCI, sseK1	G	aph4-Ia, aac-Iva, strA, strB	blaTEM-1	tet(B)	sul1	--	--	IncHI2incHI2A
		P	GEN, STR	AMP,	TET	FIS
Choleraesuis	lpfA/B/C/D/E; gogB, ratB, slrP, sspH2, sodCI, sseK1	G	strA, strB	--	tet(B)†	sul1	--	--	Col440II, incFIB, incQ1
		P	STR	--	--	FIS
Cubana	lpfA/B/C/D/E; avrA, slrP, sspH2, sseK1	G	aadA7	--	tet(A)	sul1	--	--	--
		P	STR	--	TET	FIS
Give	ratB, slrP, cdtB	G	--	--	--	--	--	--	--
		P	--	--	--	--
Heidelberg	lpfA/B/C/D/E; avrA, ratB, slrP, sspH2, sodCI	G	stra, strB, Aph4-Ia, aac-Iva, aadA2, sph, aphA2	blaTEM-1	tet(B)	sul3	---	dfrA12/ fosA	incFII, incHI2, incHI2A
		P	GEN, STR	AMP, COT	TET	FIS
Infantis	lpfA/B/C/D/E; avrA, ratB, slrP, sspH2, sseK1	G	--	--	--	--	--	--	incI1
		P	--	--	--	--
Minnesota	avrA, ratB, cdtB, slrP, sseK1	G	--	blaCMY-2	tet(A)	--	--	--	incI1, incP6
		P	--	AMP, AUG, AXO, FOX, TIO	TET	--
Manhattan	lpfA/B/C/D/E; avrA, ratB, slrP, sspH2	G	--	--	--	--	--	--	--
		P	--	--	--	--
Ohio	ratB, sspH2, sseK1	G	strA, strB, aph3''Ia	blaTEM-1, blaCMY-2	tet(A)	sul1, sul2	flo(R)	dfrA1	incA/C2
		P	STR	AMP, AUG,AXO, FOX, COT, TIO	TET	FIS	CHL
Tennessee	lpfA/B/C/D/E; avrA, slrP, sspH2, sseK1	G	aadA2	blaCARB-2	--	--	----	DfrA16/ere(A)/fosA	incN
		P	STR	AMP, COT	--	--
Typhimurium	lpfA/B/C/D/E; pefA/B/C/D; spvB/C/R; avrA; gogB, ratB, slrP, sspH2, sodCI, sseK1	G	aadA2,	blaCARB-2	tet(G)	sul1	floR	--	incFIB
		P	STR	AMP	TET	FIS	CHL
Worthington	lpfA/B/C/D/E; avrA, slrP, sspH2, sseK1	G	--	--	tet(B)	--	--	--	incI1
		P	--	--	TET	--
No of ARG			22	8	9	9	3	8

*: Predicted gene

**: Confirmed phenotype

†: Partial/truncated gene

Antibiotic used- AMP: Ampicillin, AUG: Augmentin, AXO: Ceftriaxone, AMX: Amoxicillin, AZM: Azithromycin, COT: Cotrimoxazole, CHL: Chloramphenicol, ERY: Erythromycin, FIS: Sulfisoxazole, FOX: Cefoxitin, GEN: Gentamicin, STR: Streptomycin, TET: Tetracycline, TIO: Ceftiofur

Antibiotic classes- AGly: Aminoglycosides, Bla: Betalactamases, Tet: Tetracycline, Sul: Sulfonamides, Chl: Chloramphenicol

Class 1 integrons were detected in six isolates that were grouped into five different integron profiles (ln127, in167, in363, in1581, and ln1582). Most of these integrons carried a quaternary ammonium compound resistance gene, qacE, and a sulfonamide resistance gene, sul1, as additional genes after the 3`end of the conserved segment. The class 1 integron genesin different Salmonella serovars are summarized in Table 3.

Table 3

Class 1 integrons identified in different Salmonella isolates.

Salmonella serovar	Strain name	Integron genes	Integron number	Other resistance and virulence genes on integron
Agona	CRJJGF_0019	IntI1-dfrA1-attC—gcuC-attC-3'CS	In363	sul1, qacE,
Cubana	CRJJGF_0088	IntI1-aadA7-attC-3'CS	In1581	sul1, qacE
Heidelberg	CRJJGF_0002	IntI1-dfrA12-attC—gcuF—attC—aadA2-attC-3'CS	In127	qacE*
Ohio	CRJJGF_0161	IntI1-dfrA1-attC-gcuC-attC-3'CS	In363	sul1, qacE
Tennessee	CRJJGF_0089	IntI1-dfrA16c-attC- blaCARB-2-attC-aadA2-attC-ereA1c-attC3'CS	In1582	qacE*
Typhimurium	CRJJGF_0051	IntI1-blaCARB-2—attC-3'CS	In167	qacE*

*: Partial gene

The presence of plasmids in the assembled contigs were confirmed by in silico replicon typing. The replicon type IncA/C2 was identified in MDR serovars Agona and Ohio and both these isolates harbored identical class 1 integrons In363. The replicon type IncHI2 was detected in serovars Bovisformicans and Heidelberg while IncI1 was identified in serovars Infantis, Minnesota and Worthington. The replicon type IncFII was identified in serovars Choleraesuis, Heidelberg and Typhimurium while IncN and IncP6 were detected in serovars Tennessee, and Minnesota, respectively. No replicon types were identified in serovars Cubana, Give, or Manhattan. Additional replicon col440II, and IncQ was identified in S. Choleraesuis. Eight different resistance gene clusters were detected in different Salmonella serovars and are presented in Fig 1.

Fig 1

Antibiotic resistance gene clusters in different Salmonella serotypes.

Bleomycin and EtBr resistance gene (Green) flanked by antibiotic resistance genes marked in green. The arrow shows orientation of the genes and genes are color coded to define different classes of antibiotic resistance, mobile and other genes categories.

The AR genes clusters were highly diverse, with the exception of a > 35 kb (99.9% identical) region of homologous genes carrying tetA, strA, strB, sul2, and blaCMY-2, which were detected in Salmonella serovar Agona and Ohio. The region of homologous genes carrying strA/strB, and strA/strB/sul2 were detected in Salmonella serovar Bovismorbificans and Choleraesuis respectively, while aadA/ebr/sul1 and ereA/aadA2/bla/dfrA16 were detected in Salmonella serovar Cubana and Tennessee respectively. The gene clusters aphA2/sph, and sul1/floR/tetA were detected in Salmonella serovar Heidelberg and Typhimurium respectively.

The pan-genome and functional genes comparison

Pangenome analysis was initiated using 62,730 genes of 14 Salmonella serovars that resulted into 8,174 clusters, of these 3,456 (42.3%) and 2,201 (26.9%) clusters were part of the core and accessory gene respectively. The remaining 2,517 (30.8%) independent genes identified as the unique genes. The core, accessory and unique genes are represented as inner circle, outer circle, and petals in the floral diagram respectively (Fig 2) and the details of core, accessory and unique genes in each serovars is given in S1 Fig.

Fig 2

Floral venn diagram showing the pangenome of 14 Salmonella serovars from swine.

The orthologus genes identified in all serovars presented in the center as core genes, orthologus genes identified among the serovars but not in all serovars presented in the periphery as accessary genes and each petals represents the unique genes in respective serotypes.

The unique genes among serovars ranged from 93 to 268, with highest and lowest genes in serovars Worthington and Bovismorbificans respectively. The functional distribution of genes among serovars were examined using the COG database [26]. Functions encoded by the genes in these serotypes revealed > 75% of predicted ORFs were assigned to 24 COG functional group (Fig 3).

Fig 3

Distribution of functional classes of predicted genes according to the clusters of orthologous groups in Salmonella serovars.

Different colors define different COG categories of genes.

The most abundant COG functional group among serovars was the transport and metabolism of carbohydrates (G) and the highest (426) and lowest number of genes (385) in this category was noticed in S. Typhimurium and S. Minnesota respectively. The next abundant COGs were Transcription (K) followed by amino acid metabolism and transport (E). The highest number of genes in K and E category were noticed in S. Worthington (346) and S. Ohio (381) respectively, however the lowest number of genes in K (322) and E (370) COGs were noticed in S. Minnesota. A single COG functional gene was noticed in all the S. serotypes from extracellular structure categories. The distribution of functionally characterized COG genes in core and accessory genome in Salmonella serovars (Fig 4) revealed that the functional genes in the core genome ranged 76% to 82%.

Fig 4

Distribution of clusters of orthologous groups in core, accessory and unique genes in the genomes of different Salmonella serovars.

Common numbers of core genes in each COG categories were observed and presented in Fig 4(A), The bars represents the number of clusters of orthologous groups assigned genes present in accessory (grey bars) and in the unique genes (black bars).

Uniform distributions of functional genes from different COG category was observed for core and accessory genes among Salmonella serovars. However, the percent abundances of genes in category G (carbohydrate transport and metabolism; 26–28%) and L (Replication, recombination and repair 21–23%) among accessory genomes were greater among Salmonella serotypes compared to other functional categories. The core genomes in each S. serotype were commonly enriched in COG categories D, F, H, I, J, O and Q relative to those seen in the accessory genomes.

Virulence genes, phage and CRISPR in Salmonella serovars

Genes with >95% sequence homology and coverage when compared to the virulence factor database (VFDB) were considered matches in this analysis. The complete virulence gene profiles of each Salmonella isolate is shown in S1 Table and some of the gene variants that were not detected in all the isolates is shown in Table 2. The majority of the virulence genes were detected in all the Salmonella serovars. These virulence genes were very similar, with small variations in nucleotide/amino acid sequences, while few virulence genes were missing in single or multiple Salmonella serovars. The fimbrial adherence gene operons bcfA/B/C/D/E/F/G, fimI/C/D/H, invA/B/C/E/F/G/H/I/J, csgBA and csgD/E/F/A were the most common. Most of the isolates were positive for the long polar fimbrial operon (lpfA/B/C/D/E) except Salmonella serovars Anatum, Give, Minnesota, and Ohio; however, lpfD was highly diverse among all of the Salmonella isolates. The plasmid-encoded fimbrial operon (pefA/B/C/D) and Salmonella plasmid virulence (spvB/C/R) genes were detected in S. Typhimurium and none of these genes were detected in other isolates. The pathogenicity island 1 (SPI-1), encoding type III secretion system (T3SS) secreted effector genes sipA/B/C/D, sopA, sopB, sopE2, and misL, were highly similar in all the isolates with the exception of sipD genes that shared 91% similarity to the reference gene (S. Typhimurium; NP_461804) in S. Minnesota. AvrA was identified in all the isolates except S. Choleraesuis and S. Ohio. The SPI-2 encoded T3SS genes, including spiC, sifA, sifB, sseF, sseG, sseL, pipB, pipB2, sopD2, and slrP, were detected in all the isolates. GogB was only detected in Salmonella serovars Choleraesuis and Typhimurium. Other effector genes, including ratB, sseK1, sseK2, and sspH2, were detected in some of the Salmonella serovars (S1 Table). The sspH2 effector homolog was divergent (85.52% identical) in S. Ohio. The sensory systems genes phoP/Q were identical in all the serovars with an exception in S. Worthington where a secondary mutation was observed at nucleotide position 450 (A-T) with coverage depth >50x.

Genome contents were further compared, and it was observed that several genes were confined to one serovar, or were highly diverse even if they were annotated as the same gene (S3 Table). For example a 27 kb conting in S. Agona harboring subset of type VI secretion system (T6SS). A unique pathogenesis protein, kcpA, was identified on a phage in S. Anatum. Homologs of the safA (saf-pilin pilus formation protein) was identified in 6 of the 14 Salmonella serovars (Anatum, Bovismorbificans, Cubana, Give, Johanesberg and Manhattan), but these homologs were so diverse that they were included in the list of unique genes. Highly diverse toxin-antitoxin (TA) systems type II genes were detected in different Salmonella serovars, including vapB (Agona and Typhimurium), higA (Choleraesuis and Cubana), yfjZ (Minnesota and Manhattan) and cbtA (Bovismorbificans and Tennessee). UDP-L-Ara4N formyltransferase (arnA), a bifunctional genes facilitating polymyxin resistance, was detected in S. Choleraesuis. Highly diverse colonization factor antigen I subunit E (cfaE) gene was detected in Salmonella serovar Choleraesuis, Give, Minnesota and Worthington. Microcin-M immunity protein (cmi) was detected in S. Heidelberg.

The PHASTER analysis identified intact, questionable, and incomplete phage in genomes of the Salmonella isolates. Only intact phage were analyzed in this study and a total of 52 intact lysogenic phage were predicted by PHASTER and they are listed in Table 4. Most phage were highly diverse. The most common families included relatives of Gifsy-1 (NC_010392), Gifsy-2 (NC_010393), and Salmon_SEN34 (NC_028699). Gifsy-1 like phage were detected in Salmonella serovars Bovismorbificans, Infantis, Typhimurium, and Worthington, Gifsy-2 like phage were detected in Salmonella serovars Choleraesuis, Heidelberg and Typhimurium, and the Salmon_SEN34 like phage were detected in Salmonella serovars Choleraesuis, Cubana and Give. Individual phage found in only one of the 14 included in Cubana (Entero_Psp3 [NC_005340]), Heidelberg (Escher_D108 [NC_013594]; Entero_P4 [NC_001609]), Minnesota (Entero_I2_2 [NC_001332]; Entero_SfV [NC_003444]; Salmon_vB_SemP_Emek [NC_018275]), Manhattan (Salmon_epsilon34 [NC_011976]; Entero_186 [NC_001317]) and Typhimurium (Entero_ST104 [NC_005841]). Of particular interest is the fact that some of the phage carried non-phage “cargo” genes. The AR beta-lactamase gene blaTEM-1 was seen in S. Heidelberg (Salmon_118970_sal4_NC030919), S. Ohio (Entero_lato_NC001422). The blaCARB-2 gene was seen in S. Tennessee (Entero_lato_NC001422) and S. Typhimurium (Salmon_119870_sal3_NC031940). The tetracycline gene tetC was seen in S. Anatum (Salmon_118970_sal3_NC031940); and tetA was seen in S. Cubana (Entero_lato_NC001422). The aminoglycoside gene aadA2 was seen in S. Tennessee (Entero_lato_NC001422) and S. Typhimurium (Salmon_118970_sal3_NC031940). Our analysis further confirmed that blaCARB-2 was harbored on the class 1 integrons In1582 and In167 that integrated into the possible phage Entero_lato_NC001422 (S. Tennessee) and Salmon_119870_sal3_NC031940 (S. Typhimurium), respectively. We also observed that metal resistance genes merDACPTR and silA/C/P/P2 were on the possible prophage Entero_lato_NC_001422 and Salmon_118970_sal4_NC030919 of S. Cubana and S. Heidelberg, respectively (Fig 5).

Table 4

Phage harboring virulence and resistance genes in Salmonella serovars.

S. enterica serovar	Isolate	No of Phage	Best match (kb)	Antibiotic resistance and virulence genes on Phage
Agona	CRJJGF_0019	4	Aeromo_phiO18P_NC_009542 (18.4), Entero_fiAA91_ss_NC_022750 (28.6), Salmon_vB_SosS_Oslo_NC_018279(49.9), Entero_lato_NC_001422(11)	--
Anatum	CRJJGF_0121	4	Salmon_Fels_2_NC_010463(34.2), Salmon_SPN3UB_NC_019545(46.4), Haemop_HP1_NC_001697(26), Salmon_118970_sal3_NC_031940(63.3)	sipABCD, invABCEFGHIJ, spaOPQRS, prgHIJK, sptP, sicAP, sopD,pipB2, orgBC, sicA,mig-14, mgtCtetC
Bovismorbificans	CRJJGF_0070	3	Shigel_SfII_NC_021857 (39.8), Gifsy_1_NC_010392 (55.1), Entero_lato_NC_001422 (5.6)	sodC1
Choleraesuis	CRJJGF_0148	4	Salmon_g341c_NC_013059(37.1), Salmon_118970_sal3_NC_031940(36.5), Gifsy_2_NC_010393 (33.3), Phage_Gifsy_1_NC_010392 (23.1)	sodC1
Cubana	CRJJGF_0088	3	Salmon_SEN34_NC_028699 (42.2), Entero_PsP3_NC_005340 (35.2), Entero_lato_NC_001422(66.3)	SopBtetA
Give	CRJJGF_0073	4	Salmon_SEN34_NC_028699 (29.3), Entero_mEp235_NC_019708(26.3), Pseudo_PppW_3_NC_023006(26.3), Entero_lato_NC_001422(5.3)	pipB
Heidelberg	CRJJGF_0002	4	Gifsy_2_NC_010393 (39.9), Entero_fiAA91_ss_NC_022750(33.9), Entero_lato_NC_001422(13.8), Entero_P4_NC_001609 (14.1), Salmon_118970_sal4_NC030919 (40.3)	sodC1, grvA, gtrAblaTEM-1
Infantis	CRJJGF_0031	3	Entero_SfI_NC_027339 (41.6), Salmon_vB_SosS_Oslo_NC_018279(24.3), Salmon_vB_SosS_Oslo_NC_018279(39.6)	--
Minnesota	CRJJGF_0078	6	Entero_I2_2_NC_001332 (5.2), Salmon_Fels_1_NC_010391 (14.7), Haemop_HP1_NC_001697(43.2), Aeromo_phiO18P_NC_009542 (32.8), Salmon_118970_sal3_NC_031940(44.1), Entero_lato_NC_001422 (10.7)	--
Manhattan	CRJJGF_0112	3	Salmon_g341c_NC_013059 ((41.8), Entero_186_NC_001317 (37.5), Entero_lato_NC_001422(19.9)	--
Ohio	CRJJGF_0161	2	Salmon_ST64T_NC_004348(38.6), Entero_lato_NC_001422(24.8)	blaTEM-1
Tennessee	CRJJGF_0089	3	Salmon_vB_SosS_Oslo_NC_018279 (50.8), Haemop_HP1_NC_001697(27.2), Entero_lato_NC_001422(13.7)	aadA2, ere(A), blaCARB-2
Typhimurium	CRJJGF_0051	6	Entero_ST104_NC_005841 (42.7), Gifsy_2_NC_010393 (27.8), Salmon_118970_sal3_NC_031940(47.8), Salmon_118970_sal3_NC_031940(75.1), Gifsy_1_NC_010392 (18.3), Entero_lato_NC_001422 (7.1)	gyrA, sodC1, sspH2, rck, gtrAaadA2, blaCARB-2, sul1
Worthington	CRJJGF_0141	3	Gifsy_1_NC_010392 (31.8), Salmon_SPN3UB_NC_019545(47.2), Entero_lato_NC_001422(23.5)	sspH1

*The virulence genes highlighted in bold are detected in resistance gene carrying phage

Fig 5

Examples of integrated bacteriophage.

Cargo genes are annotated, such as antibiotic and other resistance genes (Hg resistance gene [merA/C/P/T/ and mer regulators merD/R; S. Cubana], Ag resistance genes [silA/C/P/P2, SRP; S. Heidelberg], quaternary ammonium compound gene [qacC; S. Tennessee and S. Typhimurium]). The arrow shows orientation of the genes in the contigs and genes are color coded to define different gene categories.

These phage were further analyzed for the presence of virulence genes and results are summarized in Table 4. Eight of fourteen isolates harbored at least one virulence gene on phage. The comparisons for the homologous regions in prophage revealed 10 different phage shared similar regions, although these prophage were not 100% identical, but showed similarity ranging between 40 to 98%. The linear comparisons of the phage are presented in Fig 6. The identical regions were mostly part of the phage related genes.

Fig 6

Alignment of closely homologous intact integrated phage among Salmonella serotypes.

A. Phage genes synteny in five serotypes. B. Phage gene arrangement along with mobile genes (transposase, recombinase) in six serotypes. The arrow shows orientation of the genes and genes are color coded to define mobile, phage and other genes.

CRISPR loci were identified in the majority of isolates and these loci were compared for homology across serovars. The common spacers were observed towards the ancestral end of the CRISPR array e.g. common spacer was identified in eight serovars (Agona, Cubana, Choleraesuis, Heidelberg, Infantis, Manhattan, Typhimurium and Worthington). Spacer numbers varied between serovars and across the CRISPR loci (Table 5).

Table 5

Prophage target identified in spacer sequences in CRISPR arrays in Salmonella serovars.

Salmonella serovar	% identity with cas3 gene	Number of CRISPR array	Spacer
			No	Target	Gene
Agona	98.20	21	8	Prophage	Phage EaA protein
			10	Prophage	Portal protein
Anatum	98.87	24	5	Prophage	Tail tube
			8	Prophage	Phage integrase
			11	Prophage	Phage EaA protein
			15	Prophage	Phage-related protein
Bovismorbificans	45.42	23	18	Bacteria/Prophage	Integrase
		17	14	Bacteria/Prophage	Repressor
Cubana	99.32	21	6	Prophage	Bacteriophage Mu
			14	N/A	Uncharacterized protein
		9	6	Prophage	Adenine methylase
Give	45.62	15	4	Prophage	Tail fiber protein
			6	Prophage P1	DNA replication
			8	Prophage	Integrase
		18	14	Prophage lambda	ninG
Heidelberg	99.32	18	8	Prophage	Phage-related protein
Infantis	99.21	26	14	Prophage	Repressor protein
		30	7	Prophage	Phage protein
			11	Caudovirus	Capsid protein
			13	Prophage	Uncharacterized protein
			18	Prophage	DNA-binding protein
Manhattan	98.42	11	8	Prophage	Phage EaA protein
			10	Prophage	Portal protein
Minnesota	46.74	15	3	Prophage	Tail proteins
			10	Spiroplasma phage	Protein
			12	Escherichia phage RCS47	Head protein
Ohio	99.21	24	15	Prophage lambda	Terminase large subunit (GpA)
Tennessee	45.45	22	20	Salmonella phage SE1	Uncharacterized protein
			22	Salmonella phage SEN34	DNA polymerase III theta subunit
		57	17	Prophage	Terminase
Typhimurium	99.89	26	8	Bacteria/Prophage	Tyrosine recombinase xerC2
			21	Prophage	Uncharacterized protein
Worthington	97.97	28	1	Prophage	Integrase
			20	Prophage	Terminase
			23	Prophage	Tail
			26	Bacteria	Chromosome partitioning protein parB
		16	9	Prophage	Phage protein
			14	Prophage	Regulatory Protein

The sequential identical spacers towards the ancestral end was identified among these serovars for eg. two spacers detected in Salmonella serovar Cubana and Worthington, three spacers detected in Salmonella serovar Agona, Heidelberg and Typhimurium, four spacers detected in Salmonella serovar Heidelberg and Typhimurium. Unique spacer arrays were observed in serovar Minnesota, Ohio and Tennessee (the last spacer i.e. spacer 57 was identical to spacer 2 of serovar Anatum). The signature protein of the Type I CRISPR systems Cas3 gene was detected in all the S. serovars and variations were noticed in this gene when compared with S. typhimurium LT2 cas3 as summarized in Table 5. Spacer sequences were also analyzed to detect target prophage with the help of Blast using UniProt phage sequences (https://www.uniprot.org/). Prophage targets were observed in most CRISPR loci, with the most common prophage targets being tail, head, and capsid proteins. Besides this, the other targets were integrase and recombinase regions.

Discussions

The implementation of WGS allows broader inference of pathogen characteristics including prediction of antibiotic resistance and virulence profiles from the sequences. WGS has been previously used for the prediction of AR genes in a wide range of microbes including Salmonella [38]. Phenotypic and genotypic correlation analysis confirmed high concordance (97%) between phenotypically confirmed and in silico predicted AR genes. No absolute concordance was observed due to insertional inactivation if tet(B) gene in Choleraesuis and no resistance phenotype was shown by this isolate (Table 2). Resistance to aminoglycosides is either due to inactivation or modification by acetyltransferases, phosphotransferases, and nucleotidyltransferases [39]. The aac6-I variants Y and aa of was detected in all the isolates and located on the chromosome. This cryptic gene has previously been reported in Salmonella that was due to a deletion in the promoter region [40]. The strA/B and aadA genes are frequently associated with MGE that easily disseminate aminoglycoside resistance genes in Salmonella and other gram negative bacteria; streptomycin resistance has also been used as an important epidemiological marker to indicate the possibility of MDR in pathogens [41-43]. Many class 1 integrons harbor aadA gene variants [44]; four aadA variants were associated with class 1 integrons in this analysis. Other aminoglycoside resistance genes that confer resistance to kanamycin (aph(3”)-Ia) and hygromycin B (aph(4’)-Ia) were predicted in this analysis and these genes have also been previously identified in WGS data of Salmonella; moreover, aph(3”)-Ia was the most frequently detected gene from food sources [19]. All three β-lactam resistance genes (blaTEM-1, blaCMY-2 and blaCARB-2) are highly prevalent in Salmonella isolated from U.S. animals, and humans. These genes are the mostly horizontally acquired β-lactamases in Salmonella [42, 45]. Tetracycline is widely used in food animals to combat respiratory infections and have also been used as growth enhancer and an additive in feed [46](45,46). The genes conferring resistance to tetracycline are widespread among Salmonella serovars and easily transferred among wide range of microbes through HGT [47, 48]. All isolates except one with tet genes were resistant to tetracycline in this analysis and only tetracycline efflux pump genes were identified. No other tet genes (ribosomal protection protein or inactivated enzyme) were detected which suggested that the efflux pump mediated resistance was the major tetracycline resistance mechanism among these Salmonella serovars. The high prevalence of these efflux pump genes have been reported in Salmonella species [49] which further confirmed our findings (Table 2). The erythromycin resistance gene ere(A) was detected on a class 1 integrons that harbored dfrA, blaCARB-2 and aadA2 resistance determinants (Table 3). The ere(A) gene has previously been reported in class 1 integrons [50]. All dfr variants (A1, A7, A12 and A16), are associated with different profiles of class 1 integrons encoding resistance to trimethoprim. The class 1 integron carrying dfrA gene variants and other resistance genes have been reported from several Salmonella serovars Anatum, Choleraesuis, Corvallis, Eppendorf, Gallinarum, Kentucky, Rissen, Stanley, Schwarzenrund, Typhimurium, and Weltevreden [51-54]. Identical class 1 integron gene cassette (In363) were detected in Salmonella serovar Agona and Ohio (Table 3), that indicated that inter or intra species transfer of integrons help in the spread of antimicrobial resistance genes among bacteria. The fosfomycin resistance fosA gene alleles are located on the chromosome.The floR genes has been isolated from a wide range of animals and humans and it has been previously reported from various Salmonella serovars including S. Typhimurium. Chloramphenicol was used to treat MDR infections in human and animals [55-57]. The sulfisoxazole resistance genes sul1 (located within 3`-conserved segment [3`-CS] of class 1 integrons) and sul2 (associated with small multicopy plasmids or large transmissible multiresistance plasmids) are the most frequently found genes for sulfonamide resistance among sulfonamide-resistant isolates from food animals and humans, whereas sul3 is detected in various large Salmonella plasmids [58, 59]. The sulfonamide resistance genes sul1 and sul2 were the most abundant AR genes detected in this analysis, which was in accordance with the previous study where high prevalence of these genes has been reported in the MDR Salmonella isolated from animals, humans and retail meats from Northern America [60]. A secondary mutation in parC without primary mutation in gyrA is ineffective to make these isolates resistant to nalidixic acid; however, these isolates may become highly resistant once primary mutation occurs in gyrA gene as reported previously where several fold increase in resistance was observed when a secondary mutation in parC was seen in an isolate that had a primary mutation in gyrA [61, 62].

The AR genes carrying contigs were distinct and none of them were identical among Salmonella serovars except AR contigs of S. Agona and S. Ohio that shared 99.9% sequence similarity and gave best hit with virulence-resistance plasmids (incA/C2) of S. Typhimurium [63]. This >35.0 kb fragment carried tetA, tetR, strA, strB, sul2 and blaCMY-2. The strA, strB, sul2 AR genes was flanked by Tn7 elements in this partial incA/C2 plasmid and this was the most frequently recorded resistance gene combination among Salmonella serovars located on small broad-host-range plasmids, as well as detected on the chromosome in Salmonella [49]. Another 5.0 kb fragment from S. Bovismorbificans carrying strA and strB best matched with the genome of S. Enteritidis (CP020442 and CP022069) and showed 99% coverage and 100% identity to the region and appear to be widely distributed in Salmonella and other gram-negative bacteria [49]. These genes have been described as being part of transposon Tn5393 and have also been identified in bacteria circulating in humans, animals, and plants [64]. Another contig carrying aadA, ebr and sul1 was detected in S. Cubana and gave best hit with E. coli plasmid pBM0133 (KJ170699)/ pDGO101 and this array of genes is harbored by class 1 integron In1581 (Table 3) [65, 66]. The contig from S. Heidelberg that harbored neomycin (aphA2), bleomycin and streptomycin (sph) resistance genes best matched with the E. coli transposons Tn5 (U00004). These genes (aphA2 and sph) are encoded by Tn5 and used as selectable markers in cloning vectors for both eukaryotes and prokaryotes [67, 68]. A 8.69 kb contig from S. Choleraesuis carrying strA, strB and sul2 gave best hit with TY474p3 plasmid (CP002490) and it was a closed plasmid [49]. Another 5.5Kb contig carrying ereA, aadA2, bla and dfrA16 from S. Tennessee gave best hit with E. coli integron intl1 (KX57988). This integron carrying ereA and aadA2 is rarely reported [69], while a 5.0Kb fragment carrying floR and tetA in S. Typhimurium, this fragments was the part of Salmonella genomic island 1 (SGI1) that best matched with the regions of complete genome of Salmonella Typhimurium (CP028318:4845261–4850261, and CP014979:42459–47459). SGI1 has been identified in several Salmonella serovars including Typhimurium, Agona, Paratyphi B, Albany, Meleagridis and Newport [70-74]. The detection of SGI1 in different Salmonella serovars from various sources including animals and humans across the world indicates frequent dissemination of the SGI1 through horizontal transfer [75].

The size of the core genome in this analysis was in accordance with the previous studies where the size of the pan-genome expanded slightly while the size of core genome shrunken with addition of new genomes. The inter serovars core genome size (3, 224 core genes) within the 35 Salmonella subsp. enterica was lower while the intra serovar core genome size (3, 836 core genes) for S. Typhimurium was higher compared to our analysis [76, 77]. Low number of unique genes was directly related to the reduced genomes size, where HGT events were less and S. Bovismorbificans well correlated in this context with lowest numbers of unique genes and lower genome size. We could not draw any correlation between high number of unique genes and with large genome size. However, moderate genome length with high unique genes revealed its evolutionary significance. Uniform distribution of genes was noticed for other COG categories among S. serotypes. The abundance of E, G, and K cog categories of genes increases the diversity, uniqueness and their complex transcriptional regulatory networks that support morphological and physiological differentiation. The abundance of G and L functional categories of genes in dispensable genes clearly showed that these functional genes acquired for the better adaptability and diversity [78].

The majority of virulence genes were part of the core genes and essential for pathogenicity and infection. WGS data helped to correctly interpret the variations in genes among Salmonella serovars for better understanding of pathogen and evolution. This analysis clearly identified some of the genes specifically detected in one or several Salmonella serovars. For example, the pef operon comprising pefABCD genes that is needed to form structural fimbria and mediate the binding of bacteria to the microvilli of enterocytes and spvBCR that enhance virulence were solely identified in S. Typhimurium; these operons were not detected in S. Choleraesuis. However, they have been reported in virulence plasmid pSCV50 [79] harbored in S. Choleraesuis. RatB which encodes a secreted protein associated with intestinal colonization and persistence was detected in all the analyzed serovars except Agona, Anatum, Cubana, Tennessee, and Worthington [80] while gogB an anti-inflammatory effector that limits tissue damage during infection was detected in serovars Typhimurium and Choleraesuis which are predominantly associated with swine [81, 82]. Several studies have demonstrated the loss of genes associated with host specificity, thus some microbes only adapted to become a better pathogen to specific hosts while losing the ability to infect other potential hosts [83]. The lpf operon has been reported in Salmonella and is involved in the adhesion to the small intestine [84]. This operon was detected in most Salmonella serovars with high variations in lpfD genes that are highly host specific; variations in these genes could be an important factor that may influence the host range. The conserved nature of phoP/Q genes suggests that its pivotal regulatory role in Salmonella promotes several phenotypes including cationic antimicrobial peptides resistance which enhance outer membrane barrier function, and the ability to cause invasive and systemic disease [85, 86].

The genes which are confined to one serovar or their highly variable variants detected among serovars were mostly acquired genes and many of them were harbored on phage or plasmid. The T6SS is a versatile secretion system widespread among Gram-negative bacteria and directly involved in a variety of cellular processes, including virulence in several bacterial pathogens [87, 88]. Homology search resulted in best hits with Salmonella serovars Weltevreden (LN890520), Agona (CP015024), and Sloterdijk (CP012349). These loci have been reported to encode T6SS harbored on SPI-19 in Agona and Weltevreden [89]. safA plays a critical role in host recognition; highly diverse safA genes in six different Salmonella serovars confirmed that these serovars could be the part of swine asymptomatic carriers. Whereas highly identical (>98%) safA was found in S. Choleraesuis and S. Typhimurium which may recognize similar hosts as these two serovars are predominantly associated with swine [90]. The cfa gene in S. Choleraesuis was highly conserved and were identical with other S. Choleraesuis in Gen-Bank database (CP012344 and CP007639) and it may be essential for the attachment to a specific host [91]. The antimicrobial peptides encoding cmi from S. Heidelberg best matched with Escherichia coli plasmids harboring this gene (CP035337 and CP035355) and these plasmids harbored several AR genes. We believe cmi was transferred to S. Heidelberg as an accessory gene with other AR genes.

The integration of phage genetic elements in the genomes results in genome diversification of closely related bacterial strains [92] as these phage harbors AR and virulence factor that can enhance bacterial fitness [93]. Phage-associated resistance and virulence genes have been reported in Salmonella revealing the role of phage-transferred genes in pathogenicity and resistance [94, 95]. Gifsy-1 and Gifsy-2 like phage were highly prevalent among Salmonella serovars and these phage have previously been reported in Salmonella [96, 97]. In this study, we found a number of phage that encode for resistance and virulence genes. For example, we identified a 75.1 kb phage that harbor class 1 integrons carrying aadA2, blaCARB-2, sul1 AR genes and encodes a glucosyl transferases gtrA in the serovar Typhimurium, this putative virulence gene has previously been reported in P22-like and P2-like prophage in different Salmonella serovars [98].

The analysis and interpretation of the CRISPR region is complex. Spacers can only be added to the 5′ end and deleted anywhere in the locus, leaving the 3′-spacer as ancestral. The conserved spacers at the ancestral ends allowed us to understand the common infection history or common ancestory of these serovars though there is a possibility of the degradation of many internal spacers [17]. A careful analysis of CRISPR locus alignments provided an evolutionary framework to view the phylogenetic patterns of CRISPR diversity as we observed deletion of spacers in serovars Choleraesuis, Heidelberg and Typhimurium. Prophage targets were observed in most CRISPR loci; and about 87% (33/38) of spacer sequences were found to match with sequences from phage suggesting that phage were an important type of HGT in Salmonella. In this study, all eight cas genes pattern was not identified in S. Worthington as draft genome sequences was used and missing sequencing data cannot be ruled out. Cas3 involved in the cleavage of invading DNA and considered as an important component of the CRISPR mechanism and it was the only cas gene detected in all the serovars [99]. Comparison of cas3 among the serovars confirmed two distinct pattern,that was in accordance with earlier report where two distinct cas3 pattern was reported [100].

Vehicles of dissemination (plasmid, phage, integrons etc.) are crucial for microbial evolution and they play a major role in genetic innovation and genome evolution. Resistance determinants were located either on plasmids, integrons or integrons were also associated with phage which indicated that they were acquired horizontally. Highly diverse class 1 integrons containing different AR gene cassettes were detected among Salmonella serovars and these AR genes accounted for resistance to relative drugs. This suggests that these determinants of AR are functional and crucial for the survival of the microbes. A fraction of the virulence determinants were also identified on mobile elements and this suggests that these determinant are crucial for better survival. The common ancestral ends in CRISPR suggest that these isolates shared common ancestry and microbes are continuously acquiring new phage to counter the CRISPR regulation.

Conclusions

The insight into the WGS data enabled us to virtually access the genetic content for the assessment of genetic diversity, pathogenesis, evolution, serotyping, virulence and resistance profiling that enhanced our understanding of the genomic diversity among Salmonella serovars. The pangenome size was in accordance with the earlier report however the core genome was comparatively higher due to less isolates used in this analysis. Most of the virulence factors were part of the core genomes indicating absolutely required factor for virulence; however, a small fraction of virulence factors were highly diverse (safA) or confined to one isolates (cfa, pefABCD, and spvBCF) indicating variation in pathogenicity among Salmonella serovars. Inter and the intra species transferability of MGE enhance their reachability to the specific or the broader host. Variable MGE information from the WGS enables understanding of the dynamics of horizontal gene transfer carrying resistomes that were widely distributed in other Gram-negative bacteria. Detection of class 1 integrons carrying resistance determinants (In1582 and In167), high sequence diversity among related prophage carrying various resistance and virulence genes, suggesting extensive horizontal gene transfer that enhanced bacterial fitness. WGS enabled us to obtain a comprehensive resistome profile that can be useful to develop antibiotic resistance combat strategies. Comprehensive genome analysis with large dataset could profoundly enhance our understanding of the adaptability and survival mechanism in Salmonella serovars.

Virulence profiles of Salmonella serovars.

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Click here for additional data file.

Analysis of mutations in Chromosomal genes conferring resistance to antibiotics in Salmonella serovars.

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Gene content in Salmonella serovars confined to one serovars.

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Bar graph represents the distributions of the genes in core, accessory and unique gene in different Salmonella serovars from swine.

(TIF)

Click here for additional data file.

6 Sep 2019

PONE-D-19-17181

Genomic comparison of diverse Salmonella serovars isolated from swine

PLOS ONE

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Reviewers' comments:

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Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: N/A

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Gupta et al., examined the genomic profiles of diverse Salmonella serovars from swine using whole genome sequencing. Overall there are some interesting pieces, but the paper needs some major revisions and editing. Many of the specific areas of concern or further consideration are provided below.

Title

Ln3: Please remove additional ‘+’ symbol after the author name Jonathan G. Frye.

Abstract

Ln44: “More than 75% of the genes were part of the core genome”, according to Ln252 it is ~ 42% please confirm.

Ln52: Expand CRISPR.

Ln55: The keywords Salmonella and serovar can be removed and add new keywords because these two are appearing in title and arrange the keywords in descending order.

Introduction

Ln73: Please remove the” >” symbol because” more than” is already written.

Ln76-78: In general objective and hypothesis are written at the end of the introduction. However, they are written at Ln76-78.

Ln78: were Salmonella serovars collected from swine swabs?

Materials and Methods

Ln108-110: what are concentrations used for antibiotics panel used? Which solvent did used for solubility?

Results

Ln143: “This study was the part of retrospective study” were the samples used in this study obtained from the McMillan et al., 2019 (ref # 22)? It is not clear in M&M section.

Ln152-157: Data not available in Table 1.

Ln156: Expand ‘ANI’.

LN158: Expand ‘SRA’.

Ln164: Expand ‘CLSI’.

Ln172: Please correct the sentence.

Ln177-179: The information related to ‘total number of AR genes’ is not available in Table 1.

Ln178: Please include the total number of genomes before ‘genome sequences’.

Ln179-Ln182: Please recheck the result, the gene variants Y and aa of aac6-I were not found in the table 2.

Ln184: According to table2, only seven isolates were resistance to beta-lactams. Please check.

Ln198: blaCARB-2 is 2/14 right?

Ln207-209: Please check the results, the gene “ereA” is not found in Agona. Please restructure the sentence.

Ln211: “both “only in Agona both sul1 and sul2 were detected but not in typhimurium were only sul1 were detected.

Ln213: Please remove ‘chloramphenicol resistant’ or rearrange the sentence because not all the fourteen are resistance to chloramphenicol.

Ln214-215: What is the need for writing cml or cat resistance genes here because they are not detected in the study.

Ln215-220: Data not available.

Ln221: How were integrons detected? This information is not available in M & M section.

Ln231: How were plasmids detected? This information is not available in M & M section.

Ln233-237: The replicon types such as IncII, IncFII, IncN, IncP6, col440II and IncQ were not found in table 2.

Ln240-241: Please provide the complete legend for Fig.1 Example what does arrows indicated?

Ln252: The total number of unique genes 2,324 is correct? From Fig.2 they are 2,517. Please make changes.

Ln255: Please include how floral diagram is created in the M & M section?

Ln265: Please remove’(ref)’

Ln266: I could see only 22 COG functions in figure 3.

Ln269-270: Suggestions to change Y-axis as percentages and keep only most abundant functions (may be top 10 + combining all other functions).

Ln273: Please include number of genes near “highest and lowest”.

Ln275: Expand ‘E’ completely.

Ln288: Please include exact percentage values for G and L.

Ln293-328: These results are based on supplementary tables and these are presented for each isolate and it is difficult to compare the results. A comprehensive information like table 2 will help to look over the results clearly.

Ln357-359: Fig.5 results were not discussed in results section.

Ln362: This is ten right?

Discussion

Discussion is well organized however it is too lengthy, restatement of data (restatement of results) observed in some places.

References

Too many references.

Figures

Except figure 2, none of the figures are in good quality they are not clearly visible for interpretation, in addition more information is needed to add in the legend for easy interpretation.

Reviewer #2: The manuscript reports an extensive genome analysis of 14 diverse Salmonella serotypes isolated from swine using whole genome sequencing. The results suggest that majority of the genes were part of core genome and dispensable genes were acquired for adaptability. Here, the authors have performed analysis using various bioinformatics tools to identify and predict genetic repertoire in salmonella serovars. I found this paper of broad relevance to the field, especially to antibiotic resistance and public health. However, I have provided general comments and suggestions below that are necessary to improve the manuscript.

Minor comments

1. The authors have stated high concordance between phenotypically confirmed resistances and detected ARGs, however they did not state why it was not well correlated. The authors need to explain.

2. The authors noticed two distinct pattern of CRISPR-cas3 gene, how did they validated the findings ?

3. The authors have showed clusters of orthologous genes in core and accessory genes (figure 4). Authors might also consider to show the distribution of cogs in unique genes.

4. Authors might consider to add a figure showing the distribution of pan genome (core genes, accessary genes and unique genes) content in each salmonella serotypes (for eg: serovars in x-axis and number of genes in y-axis).

5. The authors need to elaborate the materials and methods sections.

6. Authors should add cogs database reference (line 265)

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Nagaraju Indugu

Reviewer #2: No

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Submitted filename: CommentToAuthorsPlosOne.docx

Click here for additional data file.

4 Oct 2019

Reviewer #1:

Gupta et al., examined the genomic profiles of diverse Salmonella serovars from swine using whole genome sequencing. Overall there are some interesting pieces, but the paper needs some major revisions and editing. Many of the specific areas of concern or further consideration are provided below.

Title

Ln3: Please remove additional ‘+’ symbol after the author name Jonathan G. Frye.

Response: We have deleted the additional + symbol in Ln3 in the revised manuscript.

Abstract

Ln44: “More than 75% of the genes were part of the core genome”, according to Ln252 it is ~ 42% please confirm.

Response: We would like to thank the reviewer for this observation, the authors want to convey that >75% of the genes in each genome were part of the core genome. To avoid confusion we have corrected the text accordingly in Ln 44.

Ln52: Expand CRISPR.

Response: CRISPR was expanded in Ln 52.

Ln55: The keywords Salmonella and serovar can be removed and add new keywords because these two are appearing in title and arrange the keywords in descending order.

Response: New key words have been added and arranged in descending order in Ln 57 in the revised manuscript.

Introduction

Ln73: Please remove the” >” symbol because” more than” is already written.

Response: “>” symbol has been deleted in Ln71 in the revised manuscript.

Ln76-78: In general objective and hypothesis are written at the end of the introduction. However, they are written at Ln76-78.

Response: We would like to thank the reviewer for this observation. The text has been deleted and added at the end of the introduction (Ln 92-97).

Ln78: were Salmonella serovars collected from swine swabs?

Response: The Salmonella serovars were from swine swabs.

Materials and Methods

Ln108-110: what are concentrations used for antibiotics panel used? Which solvent did used for solubility?

Response: All the antibiotic concentrations were as per Clinical and Laboratory Standards Institute (CLSI) recommendations. Minimum inhibitory concentrations (MICs) were manually recorded by SensiTouch®, and CLSI standards were used to determine resistance. The antibiotics were solublized in adequate solvent as per manufacturer’s recommendation.

Results

Ln143: “This study was the part of retrospective study” were the samples used in this study obtained from the McMillan et al., 2019 (ref # 22)? It is not clear in M&M section.

Response: This is a comprehensive study in which different Salmonella serovars genomes exclusively from swine were analyzed. The isolates were obtained from the previous study.

Ln152-157: Data not available in Table 1.

Response: Adequate data has been added in the Table 1 in the revised manuscript.

Ln156: Expand ‘ANI’.

Response: ANI has been expanded in the text in Ln155 in the revised manuscript.

LN158: Expand ‘SRA’.

Response: SRA has been expanded in the text in Ln157 in the revised manuscript.

Ln164: Expand ‘CLSI’.

Response: CLSI has been expanded in the text in Ln164-165 in the revised manuscript.

Ln172: Please correct the sentence.

Response: The sentence has been corrected in Ln172-173 in the revised manuscript.

Ln177-179: The information related to ‘total number of AR genes’ is not available in Table 1.

Response: The information regarding total number of AR genes has been added in Table 1.

Ln178: Please include the total number of genomes before ‘genome sequences’.

Response: We are not clear what the Reviewer is asking here. We sequenced 194 genomes from different food animals out of which 14 genomes from swine were used in this study.

Ln179-Ln182: Please recheck the result, the gene variants Y and aa of aac6-I were not found in the table 2.

Response: The chromosomally located cryptic gene aac6-IY and aac6-Iaa were uniformly detected in all the isolates. It does not confer any resistance due to mutation in the promoter region, thus these genes were not included in Table 2.

Ln184: According to table2, only seven isolates were resistance to beta-lactams. Please check.

Response: We would like to thank the reviewer for this observation. The text has been corrected in Ln184-185 in the revised manuscript.

Ln198: blaCARB-2 is 2/14 right?

Response: We would like to thank the reviewer for this comment. The digits has been corrected in Ln199 in the revised manuscript.

Ln207-209: Please check the results, the gene “ereA” is not found in Agona. Please restructure the sentence.

Response: We would like to thank the reviewer for this comment. The sentence has been restructured in Ln208-209 in the revised manuscript.

Ln211: “both “only in Agona both sul1 and sul2 were detected but not in typhimurium were only sul1 were detected.

Response: We would like to thank the reviewer for this comment. We have reframed and included the serovars details in Ln210-212 in the revised manuscript.

Ln213: Please remove ‘chloramphenicol resistant’ or rearrange the sentence because not all the fourteen are resistance to chloramphenicol.

Response: We would like to thank the reviewer for this comment. We have reframed the sentence in Ln214 in the revised manuscript.

Ln214-215: What is the need for writing cml or cat resistance genes here because they are not detected in the study.

Response: We have deleted cml or cat resistance genes.

Ln215-220: Data not available.

Response: The data has been added as a supplementary table (S2 Table).

Ln221: How were integrons detected? This information is not available in M & M section.

Response: We have added the details of integrons detection in Ln137-138 in the revised manuscript.

Ln231: How were plasmids detected? This information is not available in M & M section.

Response: We have added the tool used to detect plasmid replicon in Ln139-140 in the revised mansucript.

Ln233-237: The replicon types such as IncII, IncFII, IncN, IncP6, col440II and IncQ were not found in table 2.

Response: Plasmid replicon information has been updated in Table 2 in the revised manuscript.

Ln240-241: Please provide the complete legend for Fig.1 Example what does arrows indicated?

Response: We have added the legends for Figure 1 in the revised manuscript.

Ln252: The total number of unique genes 2,324 is correct? From Fig.2 they are 2,517. Please make changes.

Response: We have changed the total number of unique gene in Figure 2 in Ln256-257 in the revised manuscript.

Ln255: Please include how floral diagram is created in the M & M section?

Response: We have included the tool used to create floral diagram in the revised manuscript.

Ln265: Please remove’(ref)’

Response: We have added the reference in line 265 in the revised manuscript.

Ln266: I could see only 22 COG functions in figure 3.

Response: We have given details of 22 cog categories because among all the COG categories, chromatin structure and dynamics (B) category was not present in all the Salmonella serovars.

Ln269-270: Suggestions to change Y-axis as percentages and keep only most abundant functions (may be top 10 + combining all other functions).

Response: We have re structured the figure and and included the top most abundant functional group and combined all other functional group as suggested by the Reviewer in the revised manuscript.

Ln273: Please include number of genes near “highest and lowest”.

Response: We have included the number of genes in Ln277 as suggested by the Reviewer in the revised manuscript.

Ln275: Expand ‘E’ completely.

Response: We have expanded ‘E’ in Ln279 in the revised manuscript.

Ln288: Please include exact percentage values for G and L.

Response: The percentage value has been added in Ln 295-296 in the revised manuscript.

Ln293-328: These results are based on supplementary tables and these are presented for each isolate and it is difficult to compare the results. A comprehensive information like table 2 will help to look over the results clearly.

Response: All the virulence data table will be too lengthy to include, however, the genes which were not detected in all the serovars are included in Table 2.

Ln357-359: Fig.5 results were not discussed in results section.

Response: The combined results were discussed in the results section in Ln349-360.

Ln362: This is ten right?

Response: We have detected resistance and virulence genes in ten isolates, but only eight isolates harbored at least one virulence gene on phage.

Discussion

Discussion is well organized however it is too lengthy, restatement of data (restatement of results) observed in some places.

Response: The authors have restructured the sentences to avoid redundancy and shorten the revised manuscript.

References

Too many references.

Response: Some of the references have been deleted in the revised manuscript. However, we have still included many as they are important compare the findings in our study to previous work in the literature.

Figures

Except figure 2, none of the figures are in good quality they are not clearly visible for interpretation, in addition more information is needed to add in the legend for easy interpretation.

Response: We have modified the figures for clarity. We have submitted the high quality figures with 300 DPI as per manuscript requirements.

Reviewer #2:

The manuscript reports an extensive genome analysis of 14 diverse Salmonella serotypes isolated from swine using whole genome sequencing. The results suggest that majority of the genes were part of core genome and dispensable genes were acquired for adaptability. Here, the authors have performed analysis using various bioinformatics tools to identify and predict genetic repertoire in salmonella serovars. I found this paper of broad relevance to the field, especially to antibiotic resistance and public health. However, I have provided general comments and suggestions below that are necessary to improve the manuscript.

Minor comments

1. The authors have stated high concordance between phenotypically confirmed resistances and detected ARGs, however they did not state why it was not well correlated. The authors need to explain.

Response: We would like to thank the reviewer for this comment. The panel which we have used for phenotypic resistance assay contains only seventeen antimicrobials and does not include trimethoprim, chloramphenicol and fosfomycin. Hence, the authors have not included the genes conferring resistance to these antimicrobials for the correlation analysis. However, we have described rest of the resistance genes and their corresponding phenotypic resistance in the results and discussions section. We noticed high concordance between predicted resistance and detected phenotype.

2. The authors noticed two distinct pattern of CRISPR-cas3 gene, how did they validated the findings?

Response: Our analysis is based on the previous studies reporting two different cas 3 genes in Salmonella. We have aligned all the cas3 genes and constructed the phylogenetic tree which clearly clustered these isolates into two different clads.

3. The authors have showed clusters of orthologous genes in core and accessory genes (figure 4). Authors might also consider to show the distribution of cogs in unique genes.

Response: We have included the clusters of orthologous genes in unique genes and modified the figure and text accordingly.

4. Authors might consider to add a figure showing the distribution of pan genome (core genes, accessary genes and unique genes) content in each salmonella serotypes (for eg: serovars in x-axis and number of genes in y-axis).

Response: We have added the additional supplementary figure (S1 Figure) showing the distribution of pan genome (core genes, accessary genes and unique genes) content in each Salmonella serotypes.

5. The authors need to elaborate the materials and methods sections.

Response: The materials and methods section have been elaborated for more clarity in the revised manuscript.

6. Authors should add cogs database reference (line 265)

Response: The authors would like to thank the reviewer for pointing out this. The COG database reference has been included in Ln269 in the revised manuscript.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

16 Oct 2019

Genomic comparison of diverse Salmonella serovars isolated from swine

PONE-D-19-17181R1

Dear Dr. Frye,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

With kind regards,

Yung-Fu Chang

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: N/A

Reviewer #2: N/A

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thr authors have addressed all the comments and substantially improved the manuscript. I have not further comments.

Reviewer #2: All comments are addressed well in the manuscript.

An extensive genome analysis of 14 diverse Salmonella serotypes isolated from swine using whole genome sequencing was reported well. Further the authors have included a figure showing the distribution of pan genome (core genes, accessary genes and unique genes) for the readers to understand the genome repertoire of the salmonella serotypes

The authors also modified figure 4 to include clusters of orthologous genes in unique genes, as suggested. The manuscript is well written in standard English and the authors have presented a good scientific research article.

I recommend for accepting the manuscript.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

23 Oct 2019

PONE-D-19-17181R1

Genomic comparison of diverse Salmonella serovars isolated from swine

Dear Dr. Frye:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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Dr. Yung-Fu Chang

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PLOS ONE