The UMN swine group will be at the 48th AASV meeting in Denver

Next week-end will start the 48th American Association of Swine Veterinarians (AASV) meeting in Denver, CO. As usual, numerous UMN-CVM faculty and graduate students will be attending and presenting the results of their latest research. We hare looking forward  to seeing you there!

Pre-conference seminars:

  • Doug Marthaler: Porcine rotaviruses: what we know and what we are still missing
  • Maria Pieters: Current tools to approach Mycoplasma hyopneumoniae diagnostic cases

Research topics:

  • Michael Murtaugh: Broadly neutralizing antibodies to recent, virulent type 2 PRRSV isolates
  • Michael Rahe: Characterization of the memory immune response to PRRSV infection
  • Fabian Chamba Pardo: Effect of influenza prevalence at weaning on transmission, clinical signs and performance after weaning
  • Talita Resende: Mycoplasma hyorhinis associated with conjunctivitis in pigs

Antibiotic session:

  • Peter Davies: Antibiotic use metrics

Managing the reproductive herd for high health and productivity

  • Maria Pieters: A pig’s early challenges

Student session:

  • Alyssa Anderson: Use of molecular characterization tools to investigate Mycoplasma hyopneumoniae outbreaks
  • Hunter Baldry: Evaluation of positive pressure filtration to reduce aerosol transmission of PRRSV during an experimental challenge of farm access points
  • Chris Deegan: Dynamics of Mycoplasma hyopneumoniae colonization, seroconversion and onset of clinical signs in a population of gilts under field conditions
  • Zhen Yang: Investigating Porcine Circovirus Associated Disease (PCVAD) in commercial swine herd by next generation sequencing

Posters:

  • Fabian Chamba Pardo: Influenza A virus prevalence and seasonality in midwestern US breeding herds
  • Donna Drebes: Trends in Lawsonia intracellularis PCR to the submissions to the UMN-VDL over a 10-year period
  • Kevin Gustafson: B-cell tetramer monitoring of the memory immune response to PRRSV
  • Taylor Homann: Characterizing piglet loss from PRRS outbreak

 

 

Development and validation of a competitive ELISA as a screening test for Senecavirus A

An article published in the Journal of Veterinary Diagnostic Investigation (JVDI) presents a competitive Enzyme-Linked ImmunoSorbent Assay (cELISA) and a virus neutralization test (VNT), both validated for the screening of Senecavirus A in a research setting, by the National Centre for Foreign Animal disease (NCFAD). The diagnostic specificity and sensitivity were 98.2% and 96.9% for the cELISA, and 99.6% (99.0–99.9%) and 98.2% (95.8–99.4%) for the VNT, respectively.

In Canada and the USA alike, Senecavirus A is a challenge for producers and veterinarians because of its clinical similarity to Food and Mouth Disease (FMD). Indeed, Senecavirus A, is a causative agent of swine vesicular disease with lesions developing on the snout, around the mouth and on the coronary band of the feet. Therefore, being able to differentiate Senecavirus A infections from FMD rapidly is of utmost importance to be able to take the appropriate measures.

The University of Minnesota, Veterinary Diagnostic Laboratory has developed an ImmunoFluorescence Assay (IFA) to detect antibodies against Senecavirus A. This test was used as a reference for the validation of the cELISA and VNT established by Drs. Goolia, Yang, Babiuk, and Nfon from NCFAD in collaboration with Drs. Vannucci and Patnayak from the UMN-VDL.

celisa-vnt-senecavirus-a-vannucci

Abstract: Senecavirus A (SVA; family Picornaviridae) is a nonenveloped, single-stranded RNA virus associated with idiopathic vesicular disease (IVD) in swine. SVA was detected in pigs with IVD in Brazil, United States, Canada, and China in 2015, triggering the need to develop and/or validate serologic assays for SVA. Our objective was to fully validate a previously developed competitive enzyme-linked immunosorbent assay (cELISA) as a screening test for antibodies to SVA. Additional objectives included the development and validation of a virus neutralization test (VNT) as a confirmatory test for SVA antibody detection, and the comparison of the cELISA, VNT, and an existing immunofluorescent antibody test (IFAT) for the detection of SVA antibodies in serial bleeds from SVA outbreaks. The diagnostic specificity and sensitivity were 98.2% (97.2–98.9%) and 96.9% (94.5–98.4%) for the cELISA, and 99.6% (99.0–99.9%) and 98.2% (95.8–99.4%) for the VNT, respectively. There was strong agreement among cELISA, VNT, and IFAT when compared based on kappa coefficient. Based on these performance characteristics, these tests are considered suitable for serologic detection of SVA in pigs.

Link to the entire article

Using Machine Learning to Predict Swine Movements

A collaborative work between the University of Minnesota, UC- Davis, and Pipestone Veterinary Services was published this past month in the journal Frontiers in Veterinary Science.
Between-farm animal movement, despite being an essential factor of infectious disease spread is not currently recorded in the US. The objective of this project was to create a model to predict animal movement based on between-site distance, ownership, and production type of the sending and receiving farms. The model was able to predict animal movement in the south-central region of the study area with a high aggregation. It also showed an overlap with the distribution of outbreaks of porcine reproductive and respiratory syndrome (PRRS) in this area.

valdes-donoso-machine-learning-pig-movement

Abstract: Between-farm animal movement is one of the most important factors influencing the spread of infectious diseases in food animals, including in the US swine industry. Understanding the structural network of contacts in a food animal industry is prerequisite to planning for efficient production strategies and for effective disease control measures. Unfortunately, data regarding between-farm animal movements in the US are not systematically collected and thus, such information is often unavailable. In this paper, we develop a procedure to replicate the structure of a network, making use of partial data available, and subsequently use the model developed to predict animal movements among sites in 34 Minnesota counties. First, we summarized two networks of swine producing facilities in Minnesota, then we used a machine learning technique referred to as random forest, an ensemble of independent classification trees, to estimate the probability of pig movements between farms and/or markets sites located in two counties in Minnesota. The model was calibrated and tested by comparing predicted data and observed data in those two counties for which data were available. Finally, the model was used to predict animal movements in sites located across 34 Minnesota counties. Variables that were important in predicting pig movements included between-site distance, ownership, and production type of the sending and receiving farms and/or markets. Using a weighted-kernel approach to describe spatial variation in the centrality measures of the predicted network, we showed that the south-central region of the study area exhibited high aggregation of predicted pig movements. Our results show an overlap with the distribution of outbreaks of porcine reproductive and respiratory syndrome, which is believed to be transmitted, at least in part, though animal movements. While the correspondence of movements and disease is not a causal test, it suggests that the predicted network may approximate actual movements. Accordingly, the predictions provided here might help to design and implement control strategies in the region. Additionally, the methodology here may be used to estimate contact networks for other livestock systems when only incomplete information regarding animal movements is available.

Link to the full article

Advances in Mycoplasma hyopneumoniae elimination: a podcast series

This past month, the Morrison group invited Dr. Paul Yeske, swine practitioner at the Swine Vet Center (St. Peter, MN), Dr. Amanda Sponheim, PhD candidate at the University of Minnesota and Support Veterinarian at Boerhinger Ingelheim, and Dr. Maria Pieters from the University of Minnesota to discuss the latest progress made in successfully eliminating Mycoplasma hyopeumoniae from swine herds. Dr. Pieters is the head of the MycoLab at the College of Veterinary Medicine and focuses on diagnostics and epidemiology of swine mycoplasms to help veterinarians control associated diseases.

  1. History of Mycoplasma hyopneumoniae herd elimination and practices: podcast
  2. Sampling techniques and protocols to use during the process of elimination: podcast
  3. Starting the elimination: when is day zero? podcast

The podcasts in the press

Monitoring Salmonella resistance to antimicrobials in Minnesota during the past 9 years

The STEMMA laboratory at the University of Minnesota and more particularly Dr. Alvarez’s team is aiming at monitoring of antimicrobial resistance in animal and human bacteria. Therefore, the research they present in this article published this month, focused on Salmonella species both in swine and cattle. Records from the Veterinary Diagnostic Laboratory between 2006 and 2015 were compiled to study the evolution of the proportion of resistant strains of Salmonella in Minnesota.

Dr Hong, in collaboration with researchers from the U of MN, captured the number and the type of antimicrobials each strain was resistant to. He also monitored the evolution of the resistances over the nine-year period.

Evolution in antimicrobial resistant Salmonella isolates
recovered from swine at the MVDL in 2006–2015.

Explanation of the figure: Proportion of Salmonella isolates recovered from swine samples that were resistant to ampicillin (A), ceftiofur (C), enrofloxacin (E), florfenicol (F), gentamicin (G), neomycin (N), oxytetracycline (O), sulfadimethoxine (Sul), spectomycin (Sp) and trimethorpim/ sulfamethoxazole (Ts)

Abstract: Salmonellosis remains one of the leading causes of foodborne disease worldwide despite preventive efforts at various stages of the food production chain. The emergence of multi-drug resistant (MDR) non-typhoidal Salmonella enterica represents an additional challenge for public health authorities. Food animals are considered a major reservoir and potential source of foodborne salmonellosis; thus, monitoring of Salmonella strains in livestock may help to detect emergence of new serotypes/MDR phenotypes and to gain a better understanding of Salmonella epidemiology. For this reason, we analyzed trends over a nine-year period in serotypes, and antimicrobial resistance, of Salmonella isolates recovered at the Minnesota Veterinary Diagnostic Laboratory (MVDL) from swine (n = 2,537) and cattle (n = 1,028) samples. Prevalence of predominant serotypes changed over time; in swine, S. Typhimurium and S. Derby decreased and S. Agona and S. 4,5,12:i:- increased throughout the study period. In cattle, S. Dublin, S. Montevideo and S. Cerro increased and S. Muenster became less frequent. Median minimum inhibitory concentration (MIC) values and proportion of antibiotic resistant isolates were higher for those recovered from swine compared with cattle, and were particularly high for certain antibiotic-serotype combinations. The proportion of resistant swine isolates was also higher than observed in the NARMS data, probably due to the different cohort of animals represented in each dataset. Results provide insight into the dynamics of antimicrobial resistant Salmonella in livestock in Minnesota, and can help to monitor emerging trends in antimicrobial resistance.

Link to the full article