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Comparative Genomics of Drug-resistant Salmonella enterica Isolated from Dairy Cattle and HumansL. Carroll1, M. Wiedmann1, H. den Bakker2, J. Siler1, M. Davis3, W. Sischo3, T. Besser3, L. Warnick1, R. Pereira1&4
1Department of Food Science & Population Med. and Diag. Sci. , Cornell University, Ithaca, NY 2Department of Animal and Food Sciences, Texas Tech University, Lubbock, TX
3Paul G. Allen School for Global Animal Health, Washington State University, Pullman, WA4Department of Population Health and Reproduction, University of California, Davis, CA
Introduction•Salmonella spp. are estimated to cause 1.2 million illnesses each
year, approximately 450 of which result in death (6).
•Multidrug resistant isolates pose a unique threat, making the
illnesses they cause challenging to treat.
Results
Abstract
Salmonella enterica is a pathogen of concern for both humans and
cattle. It can be spread from cattle to human populations through direct
contact with animals shedding Salmonella, as well as through the food
chain. Infections caused by multidrug-resistant isolates can be
challenging to treat, making multidrug-resistant Salmonella a relevant
human health hazard. The objective of this study was to use whole
genome sequencing to study the evolutionary relationship of
antimicrobial-resistant S. Typhimurium, Newport, and Dublin isolated
from dairy cattle and humans in Washington state and New York state
from 2008 to 2012. A total of 91 drug-resistant Salmonella isolates
were selected for this study, 45 of which were from Washington state
(20 from dairy cattle and 25 from humans) and 46 from New York state
(22 from dairy cattle and 24 from humans). Isolates were selected
based on location, source, and serotype stratified by year. All isolates
were tested for phenotypic antimicrobial resistance to 12 drugs using
Kirby-Bauer disk diffusion. Genomes of all isolates were sequenced at
Cornell University using the Illumina HiSeq platform and
assembled de novo using SPAdes. In silico MLST and serotyping were
performed using SRST2 and SeqSero, respectively. SRST2 and ARG-
ANNOT were used to detect antimicrobial resistance genes in each
isolate. kSNP was used to assess overall phylogeny for the complete
set of 91 isolates. Cortex_var was used to detect SNPs within each
serotype, and maximum likelihood trees based on the variant sites were
generated using MEGA. Genotypic resistance predicted phenotypic
resistance with an overall sensitivity of 85.3% and specificity of
87.6%. Phylogenetic analyses by serotype showed evidence for
clustering geospatially and by antimicrobial resistance phenotype. By
studying the phylogenetic relationships of these isolates, we gain
further insight into the spread of drug-resistant Salmonella between
dairy cattle and humans in New York and Washington state.
Conclusions
Sample
References1. Bankevich, A., et al. SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing.
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10.1371/journal.pone.0081760.
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Antimicrobial Agents and Chemotherapy. 2014;58(1):212-20.
4. Inouye, M., et al. SRST2: Rapid genomic surveillance for public health and hospital microbiology labs. Genome
Medicine 2014, 6:90 doi:10.1186/s13073-014-0090-6.
5. Iqbal, Z., eta l. De novo assembly and genotyping of variants using colored de Bruijn graphs. Nature Genetics.
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6. Scallan, E., et al. Foodborne illness acquired in the United States--major pathogens. Emerging Infectious Diseases.
2011;17(1):7-15.
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Figure 3. Maximum likelihood trees generated using a
reference-based SNP calling pipeline.Analysis Workflow
Figure 2. Genotypic and phenotypic resistance to various
antimicrobials within each serotype-source group
kSNP v2 was used to call SNPs in the core genomes of all 91 Salmonella isolates in the data set. The resulting tree.core file was converted to a cladogram
and annotated in FigTree. Within each distinct serotype cluster, the name of each strain used as a reference sequence for subsequent within-serotype
reference-based SNP calling is denoted in black.
For each serotype, Cortex_var was used to call variants based on reference sequences S. Typhimurium str.
LT2 (RefSeq NC_003197.1), S. Newport str. SL254 (RefSeq NC_011080.1), and S. Dublin str.
CT_02021853 (RefSeq Assembly Accession GCF_000020925.1). Only calls classified as SNPs were used
to generate maximum likelihood trees using MEGA6.Genotypic resistance was determined using SRST2 and the ARG-ANNOT database. Isolates were classified as having a resistant
genotype if the antimicrobial resistance gene was detected by SRST2 with 100% sequence identity. Phenotypic resistance was
tested using Kirby-Bauer disk diffusion. Percentages were calculated using the ratio of resistant isolates to total isolates in each
serotype-source group (n = 20 for S. Typhimurium Bovine, n = 19 for S. Typhimurium Human, n = 14 for S. Newport Bovine, n =
18 for S. Newport Human, n = 8 for S. Dublin Bovine, and n = 12 for S. Dublin Human).
gDNA
extraction
and
Illumina
sequencing
91 Salmonella
isolates
Genome
assembly
(SPAdes)
Construction
of overall
phylogeny
(kSNP)
Variant calling
(Cortex_var)
In silico
serotyping
(SeqSero)
In silico MLST
(SRST2)
In silico ABR
gene detection
(SRST2 and
ARG-ANNOT)
Within-serotype
model selection
and phylogeny
(MEGA)
Kirby-Bauer
disk diffusion
for phenotypic
resistance
• Genotypic resistance predicted phenotypic resistance with an overall
sensitivity of 85.3% and specificity of 87.6% at a sequence identity threshold
of 100%.
• S. Typhimurium showed phenotypic resistance to a minimum of 1
antimicrobial and a maximum of 11. For S. Newport, the range was 6 to 10.
For S. Dublin, the range was 6 to 9.
• S. Typhimurium was the only serotype that had isolates with a nalidixic acid-
resistant phenotype, all 4 of which were isolated from humans in Washington
state.
• 12 out of 18 S. Newport isolates from New York state formed a clade with a
bootstrap value of 1.
• 28 out of 32 S. Newport isolates showed identical antimicrobial resistance
phenotypes. 3 of the 4 isolates with a non-identical resistance pattern had
additional resistance to SZD.
• S. Dublin isolates formed two large clades, one of which contained only
isolates from Washington state. 7 of 10 of these isolates had identical
antimicrobial resistance phenotypes.
Figure 1. Cladogram generated using all SNPs called within the core
genomes of all 91 Salmonella isolates.
S. Typhimurium
S. Newport
S. Dublin
S. Typhimurium
S. Newport
S. Dublin
AntimicrobialSensitivity
(%)
Specificity
(%)
AmClav 89.5 80.0
Amp 100.0 75.0
Cefo 98.5 91.7
Ceft 87.0 95.5
Ceftr 95.7 90.9
Chlo 98.6 94.7
Nal 0 95.5
Strep 78.4 66.7
Sulf 98.8 88.9
SZD 100 97.6
Tet 91.6 87.5
Overall 85.3 87.6
Table 1. Analysis of
genotype prediction of
phenotype resistance in
Salmonella isolated from
cattle and humans.
Washington state only
New York state only
(bootstrap value = 1)
SZD-resistant isolates
AcknowledgmentsThis material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under grant no. DGE-1144153.
Research reported in this publication was also supported by the Agriculture and Food Research Initiative Competitive Grant no. 2010-51110-21131 from the USDA
National Institute of Food and Agriculture. The content is solely the responsibility of the authors and does not necessarily represent the official views of the USDA.
The authors would like to thank Drs. Matt Stasiewicz, Jasna Kovac, and Michael Stanhope for their help with this project.
Phenotypic Antimicrobial resistance profiles
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AmClav Amp Cefo Ceft Ceftr Chlo Nal Strep Sulf SZD Tetra
Perc
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S. Dublin Bovine
S. Newport Bovine
S. Typhimurium Bovine
S. Dublin Human
S. Newport Human
S. Typhimurium Human