Prevalence, quantity and antibiotic resistance profiles of Salmonella enterica in response to antibiotic use early in the cattle feeding period Gizem Levent Department of Veterinary Pathobiology College of Veterinary Medicine and Biomedical Sciences
Introduction- Salmonella Gram negative, rod shaped Animals and environment Enterobacteriaceae family Salmonella enterica sp. o 6 subspecies, over 2500 serovars http://www.medicalnewstoday.com/articles/160942.ph p
Introduction- Salmonellosis Infection with nontyphoidal serovars of Salmonella The CDC estimates that 1.2 million human illnesses occur annually due to salmonellosis in the United States Poultry and eggs are the main cause of the salmonellosis cases; however, beef is also a cause of Salmonella outbreaks. Laufer et al., Epidemiol. Infect., 2015
Introduction- Antibiotic resistance CDC, antibiotic resistance threats in the United States, 2013 CDC, antibiotic resistance threats in the United States, 2013
Introduction- Antibiotic use Reasons of antibiotic use in farm animals Therapeutic Metaphylactic Prophylactic Growth promotion FDA, 2014 SUMMARY REPORT on Antimicrobials Sold or Distributed for Use in Food-Producing Animals
Objective Determine the long-term effects of tulathromycin and ceftiofur treatment on Salmonella enterica prevalence, quantity and antibiotic resistance profiles in cattle feces throughout the feeding period, and on hides and in lymph nodes at slaughter.
Antibiotics Ceftiofur and tulathromycin are two antibiotics that are used to treat bovine respiratory disease (BRD) in cattle Ceftiofur crystalline-free acid (Excede ) Third-generation cephalosporin Same class as ceftriaxone Tulathromycin (Draxxin ) Semi-synthetic macrolide Same class as azithromycin
Antibiotics Adapted by Doyle et al, 2013 from WHO CIA List, 3 rd revision, 2012
Materials and methods- Study design Each pen: 11-12 cattle (10 treatment, 1-2 control) Randomized and starting weigh blocked trial Modeled at individual level with random pen level effects
Materials and methods- Sampling Fecal samples were collected on Day 0, 7, 14, 28, 56, 99 and the day before slaughter 1m 2 Hide brisket area of each cattle was swabbed a day before the slaughter Both Subiliac lymph nodes from each cattle were collected at the slaughter Timeline of the study (not to scale)
Materials and methods- Transportation and storage Kept in cold chain Overnight shipment Feces were preserved with and without glycerol upon arrival Hide and lymph nodes were processed freshly upon arrival and preserved with and without glycerol Frozen at -80ºC Transportation feces and hide Transportation lymph nodes Storage feces Storage lymph nodes
Materials and methods- Quantification and isolation Step 1: Preparation of fecal samples, lymph nodes and hide swab suspensions Step 2: Spiral plating and colony counting Step 3: Prevalence estimation and isolation by using specific enrichment broths and agar. Preservation into the beads for storage at -80 ºC Step 4: Confirmatory tests; Serum O- antigen test and Maldi-TOF analysis
Materials and methods- Phenotypical antimicrobial susceptibility Micro dilution method TREK Sensititre system Gram negative- NARMS panel plates Cefoxitin Ceftiofur Ceftriaxone Azithromycin Chloramphenicol Tetracycline Amoxicillin/ Clavulanic acid Ciprofloxacin Gentamicin Nalidixic acid Sulfisoxazole Trimethoprim/ sulfamethoxazole Ampicillin Streptomycin
Materials and methods- Statistics STATA ver. 12 Prevalence, quantification and antibiotic resistance comparisons of Salmonella by day and treatment: Descriptive statistics Mixed linear (log 10 CFU) and logistic (prevalence) regression Main effects full factorial models Ceftiofur and tulathromycin Day Random effect Pen level
Results- Descriptive statistics 898 stool, 224 lymph nodes and 132 hide samples were collected. 799 stool samples from (Day 0, 7, 14, 56, 99) and 132 hide and 224 lymph node samples had been processed at the time of publication. Overall, Salmonella prevalence estimates were 42.5% (340/799) in feces, 75.4% in lymph nodes (169/224) and 84.0% in hide samples (111/132).
Results- Descriptive statistics In total, 620 isolates were tested by micro broth dilution; 108 isolates were resistant to 1 class of antibiotic 5 isolates were resistant to 2 antibiotics 6 isolates were resistant to 3 class of antibiotics
Results- Descriptive statistics Based on the Maldi- TOF results; after the enrichment among 343 fecal Salmonella suspected isolates; 340 were confirmed as Salmonella spp. Other 3 were Citrobacter sedlakii. Lymph and hide isolates were all detected as Salmonella spp. Maldi- TOF analysis have been also run on few isolates which were found interesting in the lymph nodes Klebsiella pneumoniae Leclercia adecarboxylata Enterobacter cloacae
Results- Multi level mixed-effects linear regression
Results- Multi level mixed-effects linear regression
Results- Multi level mixed-effects logistic regression
Results- Multi level mixed-effects logistic regression
Conclusion and future work The overall highest Salmonella prevalence was from hide samples when compared with lymph nodes and fecal samples; however, fecal samples were acquired from late winter through late summer months whereas hide and lymph node samples were only acquired during the hottest months of the year. The vast majority of Salmonella isolates were pansusceptible or singly resistant (e.g., to tetracycline) and this was unaffected by treatment. Season was the strongest effect on increased prevalence of Salmonella, likely due to increased ambient temperature affecting bacterial survival and replication outside the host. Treatment effect of antibiotics did not carry over to the end of feeding period in impacting prevalence or quantity of Salmonella in lymph nodes. The CFU of Salmonella in feces at the end of the feeding period did not differ among treatment groups. Sequencing and serotyping the Salmonella isolates will be the next step to be able to have a further understanding of the distribution and the prevalence of the Salmonella serotypes among fecal samples during the feeding period, among hide samples and lymph node samples at the slaughter.
Acknowledgements Dr. H. Morgan Scott -TAMU Dr. Sam E. Ives -WTAMU Dr. Robin C Anderson -USDA Dr. Sarah D. Lawhon -TAMU Dr. Guy H. Loneragan TTU Dr. Keri Norman TAMU H.M Scott Lab Support Dr. Javier Vinasco, Roberta Pugh Naomi Ohta,Franklin Lopez Maribel Leon, Sarah Murray Selma Gonzalez, James Ogunrinu Ethan Taylor, Jessica Morales Anisa Wakil Feedlot support Ashlynn Schlochtermeier-WTAMU Rebecca Parrish- -WTAMU Samantha Foos- -WTAMU Grant Support This work has been supported in part by a contract from the Beef Checkoff.
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