AntimicrobialresistancetrendsinnorthernCaliforniadairycattleSalmonella isolates,2002-2016

Background

Objective

Results Discussion

Acknowledgements

References

• Nontyphoidal Salmonella infections contribute to 1.2million annual illnesses in the United States1

• Salmonella is a significant foodborne pathogen; humanoutbreaks have been associated with dairy products,ground beef, and contact with dairy cattle2,3,4

• Salmonella antimicrobial resistance (AMR) is a seriousconcern that can increase recovery time, medical costs,and mortality rates in humans and animals1

• Surveillance data of AMR in Salmonella isolated fromcattle can aid in improving treatment plans, managingcurrent AMR, and preventing future AMR development

Identify trends in AMR phenotype of Salmonella isolatesobtained from dairy cattle fecal samples at the University ofCalifornia, Davis Veterinary Medical Teaching Hospitalmicrobiology laboratory from 2002 to 2016

KellyE.Davidson*,RichardV.Pereira1,BarbaraA.Byrne2UniversityofCalifornia,Davis• SchoolofVeterinaryMedicine•PopulationHealthandReproduction1 •Pathology,Microbiology&Immunology2

• Multidrug resistance (MDR) was observed in50.8% of Salmonella isolates

• Three, similar MDR patterns were observed in29.3% of Salmonella isolates. The mostcommon was a pattern of nine antimicrobials(Table 1). The second and third most commonpatterns included the same nine drugs inaddition to either trimethoprim/sulfisoxazole orgentamicin.

• Significantly higher odds for resistance toaminoglycosides, beta-lactam/beta-lactamaseinhibitor combinations, folate pathwayinhibitors, penicillins, and tetracyclines wereobserved for the 2002-2009 period whencompared to the 2010-2016 period

• Cephalosporins, quinolones, and macrolides (allantimicrobial classes containing medicallyimportant drugs) did not show a significantchange in AMR between the 2002-2009 and2010-2016 periods.

Boehringer-Ingelheim Veterinary Scholars Program

U.S. Department of Agriculture Project number CA-V-PHR-4069-H“Any opinions, findings, conclusions, or recommendations expressed in thispublication are those of the author(s) and do not necessarily reflect the view of theU.S. Department of Agriculture”

University of California, Davis Veterinary Medical Teaching HospitalMicrobiology Laboratory

Conclusion

1 Antibiotic Resistance Threats in the United States, 2013. 71-72 (Centers for Disease Control and Prevention, 2013).2 Gould, L. H., Mungai, E. & Behravesh, C. B. Outbreaks attributed to cheese: differences between outbreaks caused by unpasteurized and

pasteurized dairy products, United States, 1998-2011. Foodborne Pathog Dis 11, 545-551, doi:10.1089/fpd.2013.1650 (2014).3 Multistate Outbreak of Salmonella Typhimurium Infections Linked to Ground Beef (Final Update),

<https://www.cdc.gov/salmonella/2011/ground-beef-2-1-2012.html> (2011).4 Multistate Outbreak of Multidrug-Resistant Salmonella Heidelberg Infections Linked to Contact with Dairy Bull Calves (Final Update),

<https://www.cdc.gov/salmonella/heidelberg-11-16/index.html> (2017).5 OPS Diagnostics. Available at http://opsdiagnostics.com/images/products/1253.jpg. Accessed July 22, 2017.6 Avena Medica. Available at http://www.avena-medica.com/ProductVault/product_1351076952__mg_3625_S4.jpg. Accessed July 22, 2017.7 Microbe Online. Available at http://microbeonline.com/types-of-bacteriological-culture-medium/. Accessed July 22, 2017.8 Karter Scientific. Available at https://www.kartersci.com/16x100mm_Test_Tubes_Borosilicate_Glass_Round_Btm_p/402f2.htm. Accessed

July 22, 2017.9 EdgeBio. Available at https://www.edgebio.com/sites/default/files/96-Well%20Treated%20Microplates%20V-bottom.jpg. Accessed July 22,

2017.10 Bruker. Available at https://www.bruker.com/fileadmin/_processed_/csm_microflex-lt-product-banner_1d453de04d.jpg. Accessed July 22,

2017.

Despite reduced odds of AMR to many drug classesin the 2010-2016 period, lack of a significantreduction in AMR for important drug classes such ascephalosporins, quinolones, and macrolideshighlight the relevance of continual AMRsurveillance in cattle with Salmonella infections totarget future interventions.

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Figure 1. Nonsusceptibility prevalance to aminoglycoside antimicrobials exhibits adecreasing linear trend from 2002-2016. There are significantly higher odds fornonsusceptibility to aminoglycosides for the 2002-2009 period when compared to the 2010-2016 period (OR: 2.03, 95% CI: 1.1 – 3.7).

Figure 2. Nonsusceptibility prevalence to nalidixic acid is minimal, and nonsusceptibilityprevalence to other beta-lactam antimicrobials and a beta-lactam/beta-lactamaseinhibitor combination exhibit decreasing linear trends from 2002-2016. There aresignificantly higher odds for nonsusceptibility to amoxicillin/clavulanic acid (OR: 1.79, 95%CI: 1.0 – 3.4) and ampicillin (OR: 1.87, 95% CI: 1.0 – 3.5) for the 2002-2009 period whencompared to the 2010-2016 period. There is no significant difference in odds fornonsusceptibility to cephems for the 2002-2009 period when compared to the 2010-2016period (OR: 1.65, 95% CI: 0.9 – 3.1). Nonsusceptibility to nalidixic acid occurs only in the2010-2016 period.

Figure 3. Nonsusceptibility prevalence to folate pathway inhibitors exhibits adecreasing linear trend from 2002-2016. There are significantly higher odds fornonsusceptibility to folate pathway inhibitors for the 2002-2009 period when compared tothe 2010-2016 period (OR: 2.45, 95% CI: 1.3 – 4.5).

Figure 4. Nonsusceptibility prevalence to chloramphenicol and tetracycline exhibitdecreasing linear trends from 2002-2016. There are significantly higher odds fornonsusceptibility to tetracycline for the 2002-2009 period when compared to the 2010-2016period (OR: 1.87, 95% CI: 1.0 – 3.4). There is no significant difference in odds fornonsusceptibility to chloramphenicol for the 2002-2009 period when compared to the 2010-2016 period (OR: 1.54, 95% CI: 0.8 – 2.8).

00.10.20.30.40.50.60.70.80.91.0

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Figure 5. Salmonella serotypes Dublin, Newport, and Typhimurium displaynonsuceptibility to ceftriaxone in multiple years of the study period. SerotypesNewport, Dublin, and Typhimurium are also the most common serotypes observedthroughout the study period, making up 21.5%, 19.0%, and 9.1% of serotypes, respectively.

Table 1. Susceptibility patterns of 242Salmonella isolates to the NARMS†

gram-negative antimicrobial panelare varied, with nonsusceptibility toceftriaxone observed in 40.1% ofisolates.

Au = amoxicillin/clavulanic acidA = ampicillinF = cefoxitinX = ceftiofurCx = ceftriaxoneC = chloramphenicolG = gentamicinN = nalidixic acidS = streptomicinSu = sulfisoxazoleT = tetracyclineT/S = trimethoprim/sulfimethoxazole

All isolates were susceptible to azithromycin andciprofloxacin.

Methods

Plates read using Sensititre VizionSystem®

24-hour, CO2 incubation

18-hour, non-CO2 incubation

Inoculate 2-3 colonies

4-6-hour, non-CO2 incubation

Inoculate

MH broth

Inoculate

Inoculate18-hour, non-CO2 incubation

MALDI-TOFindividual colony ≥ 24 hours old

Isolation streaking frozen stabilates of Salmonella isolates on blood agar

Plate on blood agar as QC*

Serotyping of Salmonella isolates conducted using standard protocols by National Veterinary ServicesLaboratories in Ames, Iowa. Antimicrobial susceptibility testing followed Clinical Laboratory StandardsInstitute (CLSI) guidelines.

References for photos: 5, 6, 7, 8, 9, 10; *QC = quality control; †NARMS = National Antimicrobial Resistance Monitoring System

SusceptibilityPattern Count PrevalencePansusceptible 78 0.322AuAFXCxCSSuT 38 0.157Su 34 0.141AuAFXCxCSSuTT/S 17 0.070AuAFXCxCGSSuT 16 0.066AuAFXCxSSuTT/S 10 0.041ASSuT 8 0.033CSSuT 8 0.033AuAFXCxCGSSuTT/S 7 0.029ACSSuT 6 0.025AuAFXCxCGSuT 6 0.025S 6 0.025ACGSSuTT/S 2 0.008AuAFXCxCNSSuT 1 0.004AuAFXCxCNSSuTT/S 1 0.004AuAFXCxSSu 1 0.004CGSSuT 1 0.004FCGSSuTT/S 1 0.004SSu 1 0.004Total 242 1

Sterile saline

BHI brothBHI broth

NARMS†,gram-negativepanel