The MSHMP team, led by Dr. Carles Vilalta published a new article in the Journal of Veterinary Diagnostic Investigation regarding the effect of pooling on the detection of PRRS in processing fluids.
The MSHMP team has been one of the first to publish data on the detection of PRRS in processing fluids. You may find all of our previous articles on processing fluids here.
Objectives of the study
- Identify the limit of PRRS virus detection in pooled processing fluids
- Evaluate the effect of pooling on the initial Ct value
Study 1: What is the maximum number of processing tissues that we can aggregate and still detect one PRRS-positive set?
Tails (and testes for the males) from 40 piglets were kept in individual tubes. Processing wounds were swabbed and tested for PRRS by PCR. Three individual piglets were selected, one male with a Ct<25, and one male and one female with a Ct>25. No female with a Ct<25 was found in that group. Tissues from each of these three piglets were mixed in their own bag with tails and testes from around 120 naive piglets (10 litters). The three bags were stored for 24 hours in a fridge. At that time, 4mL of the fluids in each bag were tested for PRRS by Rt-PCR. At that time, processing tissues from 10 litters were added to each bag. After mixing and 24 hours in a fridge, 4mL were collected and tested for PRRS by PCR. The process was repeated until tissues from 50 naive litters were added.
All the agglomerated processing fluids including the one tail from a positive female piglet came back negative for PRRS by Rt-PCR.
Regarding the agglomerated samples with the one male tissue with high Ct-value, agglomerated processing fluids came back positive up to 40 litters added to the initial tissues. Only the sample with 50 litters plus the original positive tissues came back negative.
Lastly, all of the agglomerated samples including the tissues from the male piglet with a low Ct-value came back positive for PRRS by PCR. This means that fluids from one set of positive testes and tail mixed with processing tissues from around 600 naive piglets were PRRS positive by PCR.
Study 2: Pooling and diluting effect on processing fluids
Eight PRRS PCR positive samples were diluted five times each (10, 20, 30, 40, and 50 times). The dilutions were then tested for PRRS by Rt-PCR.
Overall, the Ct-value increase by 4.6 in average between the initial sample and the one diluted 10 fold for the eight selected samples. Ct-values increases by 1.4 between the 10-fold and 50-fold dilutions. There was no difference in the results based on the Ct-value of the initial processing fluid sample (below or above 25). That being said, the sensitivity varied a lot based on the initial Ct-Value. Indeed, if the initial Ct-value was around 30, it took 22 dilutions for the sample to fall in the suspect range whereas 40% of the time, samples with an initial Ct-value of 30 will fall in the negative category after 20 dilutions. Similarly, 5% of the sample with an initial Ct-value of 35 were above a Ct-value of 40 after 10 dilutions. This number increase to 39% after 20 dilutions.
A sampling technique has been validated to monitor porcine reproductive and respiratory syndrome virus 2 (PRRSV-2) using the serosanguinous exudate known as processing fluids (PFs) that accumulate from tissues obtained during tail docking and castration. PFs are an aggregate sample of large numbers of piglets and litters. However, little is known about the effect of litter aggregation on the ability of PCR to correctly classify an aggregated PF sample as positive. We evaluated both the effect of litter aggregation and of PF pooling on PCR detection. We estimated that aggregation of at least 50 litters was possible when a pig with a Ct value of ~22 was present in the sample, and aggregation of up to 40 litters was possible when there was a sample with a Ct value of ~33. Pooling did not affect PCR detection when initial Ct values of 20 and 25 were assessed. However, in litters with initial Ct values of ≥30, the amount of pooling should be reduced. Our results provide producers and practitioners with a general framework to interpret more accurately the results of their PRRSV-2 surveillance programs using PF.