Introduction
Respiratory disease in nurseries is one of the most common problems of
weaned pigs. These processes have
complex
aetiology involving both viral and bacterial agents. The most common
clinical picture of respiratory disease in nurseries is characterized by
cough, with or without fever. Nasal discharge, laboured breathing, and
increased mortality may be present as well. Since several agents may
produce similar lesions, the pathological picture only has an indicative
value and do not allow a precise diagnosis. In many nurseries, these
respiratory disease outbreaks, are recurrent batch after batch implying
an increased use of antimicrobial agents to treat complications .
Viral pathogens are generally considered the primary agents of
respiratory disease in nurseries. In the field, several respiratory
viruses can circulate simultaneously in nurseries, making it difficult
to ascertain the role of each one in the outbreaks and their
interactions in a particular case. For some pathogens such as swineInfluenza A virus (swIAV), a primary role in respiratory
outbreaks can be assumed despite the variable virulence of different
strains. For some other agents, such as the Porcine respiratory
coronavirus (PRCV), it is more difficult to establish their role,
whether primary or not, in causing respiratory disease (). Additionally,
some viral agents, such as Porcine circovirus 2 (PCV2) andPorcine reproductive and respiratory syndrome virus (PRRSV), may
have immunosuppressive or immunomodulatory capabilities, impairing or
modifying the response to other agents . The immunosuppressive
capabilities of Porcine cytomegalovirus (PCMV) have not been
fully proven, although PCMV is supposed to regulate the expression of
different cytokines (IL-1, IL-2, IL-12, TNF-α, and IL-10) .
Bacterial agents can participate in the respiratory disease of weaners
as well. Some may be the primary agents, e.g., Mycoplasma
hyopneumoniae , while others may act mainly as synergistic agents. The
interactions leading to such complications are poorly understood and the
evidence available is contradictory .
The scientific consensus indicate that the clinical and pathological
picture of the respiratory farm outbreaks will be the result of the
interaction of different viruses and bacteria with a host of a given
genetic background and immune status under the environmental
circumstances of the farm (See for an excellent review).
In the last years, several viruses have been added to the list of
potential respiratory pathogens of pigs. Among them, Influenza B (IBV)
and D viruses (IDV) , swine orthopneumovirus (SOV) ,Porcine parainfluenza 1 virus (PPIV1) also designated asPorcine respirovirus , and Porcine circovirus 3 (PCV3) are
worth mentioning. The knowledge on the epidemiology of these viruses and
their participation in respiratory outbreaks is limited with only a few
reports available The role of other recently discovered agents such as
PCV4 is not known yet .
The present study aimed to explore the participation of several
respiratory viruses, including the recently reported SOV, PPIV, PCV3,
and PCV4 together with IBV and IDV, in respiratory outbreaks that were
initially sent to the laboratory under suspicion of swIAV infection.
Material and methods
Cases and sample collection
The study comprised 55 respiratory outbreaks in nurseries (out of the 84
cases received for diagnosis between 2017 and 2019) from which nasal
swabs (n=873, no less than 10 samples per case) were submitted for
diagnosis. Outbreaks were defined
as situations with noticeable respiratory disease and where predominant
signs were cough and fever.
These cases have been previously examined for swIAV during a
surveillance of this infection in Spanish farms . The 55 studied
outbreaks were comprised of 29 randomly selected outbreaks with
swIAV-positive animals and 26 randomly selected swIAV-negative cases.
Nasal swab suspensions were pooled (3 samples/pool) for the initial
analysis of respiratory viruses. For each pathogen found to be present,
10 random positive farms were selected and animas were analysed
individually. Each farm was assigned a 1-letter code.
Additionally, since some farms performed routine monitoring of swIAV in
farrowing crates and nurseries, we had the opportunity to test the
circulation of respiratory viruses at different ages on the same farm in
8 additional cases. This sampling comprised 20 nasal swabs collected in
farrowing units and 12 in nurseries. With those numbers, any agent could
be detected if present in ≥ 15% or ≥25% of the animals, farrowing
units and nurseries, respectively with 95% confidence. These samples
were examined initially by pooling (3 samples/pool).
RNA extraction and RT-PCR
RNA was extracted using MagMax Core nucleic acid extraction kit
(ThermoFisher Scientific) according to the manufacturer’s instructions.
Presence of the different viruses was examined by real time PCR or real
time RT-PCR using the AgPath-ID One-Step RT-PCR Reagents (ThermoFisher
Scientific). Detection of swIAV, IBV and IDV, and PCV2, PCV3, and PCV4
was done using the previously described primers . For PPV1, PCMV, PRCV,
and SOV, the primers were designed specifically for this study (see
table 1). To evaluate the specificity of these primers, positive samples
for each one of these viruses were amplified by conventional RT-PCR (see
primers in table 1) and sequenced by SANGER sequencing. BLAST was
carried out to identify the sequence. The presence of PRRSV was assessed
using LSI VetMax PRRS EU/NA v2 reagents. To evaluate farm prevalence
with more precision, individual samples from 10 outbreaks positive for
each pathogen were also analysed by RT-PCR.
Statistical analysis
A farm was considered to be infected by a given virus if at least one
sample was positive for that virus. The associations between pathogens
were tested by means of the χ2-test considering all other pathogens as
potential confounding variables (stratified analysis). In a second step,
the probability of two pathogens being associated by outbreak was also
analysed. Additionally, a k-modes cluster analysis was carried out using
Rstudio to evaluate associations of two or more pathogens in respiratory
outbreaks.
Individual results from 10 outbreaks were used to determine the
prevalence of these viruses in respiratory outbreaks. In this case,
average and distribution of Ct-values were also compared by means of
Kruskal-Wallis test.
All statistical comparisons using χ2-test and Kruskal-Wallis were done
using the StatsDirect software, and cluster analysis was carried out in
R software, version 4.1.1, using K-modes script.
Results
Prevalence and association of respiratory viruses PRRSV,
PRCV, SoV, PCV2, PCV3, and PCMV in swIAV-positive and -negative
nurseries.
The final sampling comprised 55 respiratory farm outbreaks, of which 26
happened in swIAV-positive nurseries. Globally, PCV3 was the most
frequently found virus, present in 43/55 outbreaks (78.2%;
CI95%: 66.6-87.8%). PRRSV and PCMV were found in 40/55
outbreaks (72.7%; CI95%: 58.8-83.5%); PRCV was found
in 29/55 outbreaks (52.7%; CI95%: 39.3-66.1%); PCV2
was found in 18/55 outbreaks (32.7%;
CI95%:21.1-46.8%); and SOV was found in 17/55
outbreaks (30.9%; CI95%:19.5-45.0). Influenza B,
Influenza D, PCV4, and PPIV1 were not detected in any of the outbreaks.
To note, this is the first description of SOV occurrence in pig herds in
Spain.
Figure 1 shows the proportion of cases in which each pathogen (PRRSV,
PRCV, SoV, PCV2, PCV3, PCMV) was found based on the swIAV status of the
farm. Interestingly, the frequency of a given pathogen in the
swIAV-positive and -negative outbreaks (on a herd level) was different.
PRCV, SOV, and PCMV were more likely to be found in swIAV-positive
outbreaks (69.2% vs. 37.9%; 46.2% vs. 19.2% and 88.5 vs. 58.6%,p <0.05, respectively, for the three pathogens
considering swIAV-positive versus negative). In the 55 farms, 31
different combinations of the examined viruses were detected
(Supplementary table 1). In one respiratory outbreak no virus was found.
In the next step, the probability of two pathogens being associated in
the outbreaks was analysed. The results (Table 2) suggested that
swIAV-positive nurseries were more likely to be infected by PRCV, SOV
and PCMV. SOV-infected nurseries were more likely to have PCMV or
PRCV-positive animals (Table 2). Moreover, PCMV and PRCV were also
statistically associated (p<0.05). The k-mode cluster analysis
indicated that three clusters of outbreaks could be recognized based on
the participation of different pathogens: Cluster 1 comprised outbreaks
with the presence of swIAV, PRRSV, PRCV and SOV (n=7), Cluster 2 were
cases positive for swIAV, PRRSV, and PRCV, and negative for SOV (n=4);
and Cluster 3 included cases positive for PRRSV and PCMV, and negative
for all the other pathogens (n=5). Globally, the cluster analysis
explained just 16/55 cases (29.1%).
Prevalence and association of pathogens swIAV, PRRSV, PRCV,
SoV, PCV2, PCV3, and PCMV on an individual level
To have further insight on the prevalence of each pathogen, we then
performed the analysis at the individual level. Ten batches (one batch
of each farm) of infected nurseries for each pathogen were selected; the
average Ct values of each pathogen are shown in Figure 2 and
supplementary material 2. As a result, a diversity of Cts (from 15-16 up
to 30s) could be found for most of the examined viruses, while it was
very uncommon to obtain Ct values of PCV2 and PCV3 below 30. On average,
the individual prevalence levels for the different viruses were as
follows: swIAV 48.6%; PRCV 48.0%; PRRSV 31.6%; SOV 33.8%; PCMV
48.3%, PCV2 36.0%; PCV3 33.0%.
The association between different pathogens at the individual level was
analysed as well. As shown in Table 3, PRCV was the pathogen with the
most associations. It had positive interactions (p <
0.05) with swIAV and SOV but a negative association (p< 0.05) with PRRSV and PCVM. Besides these, swIAV and PRRSV
were negatively related (p < 0.05).
To examine whether the infection started from the maternal stage, 8
farms where suckling pigs and weaners had been sampled were analysed. In
this part only SOV, PCV3, PCMV, and PRCV were included because for
swIAV, PRRSV, and PCV2 it is well known that viral circulation may start
in maternities. The analysis of the nasal swabs indicated that PCMV
spreads mainly in nurseries since the frequency of positive pools in 7/8
farms reached 100% in that phase (Figure 3). In contrast, for SOV,
PCV3, and PRCV the infection was mostly found in suckling pigs,
suggesting the role of sows in transmitting the infection.
Discussion
The polymicrobial nature of the porcine respiratory disease complex is a
well-established and widely-accepted concept. Nevertheless, the
participation, contribution and interaction between different agents in
that complex is not so well understood. One of the main reasons for
this, is the difficulty in establishing experimental models that can
reflect the complexity of the population in a herd as well as the
factors and events that take place in the farm. Moreover, the use of
molecular techniques allowed the discovery of new agents. In pigs, the
number of viruses known to potentially participate in the respiratory
disease has increased with the discovery of IBV, IDV, PPIV1, SOV, PCV3
and PCV4
In the present study, we examined the presence of a panel of 11 viruses
in outbreaks of respiratory disease in nurseries. The cases included in
this work had been initially submitted for the diagnosis of swIAV
because of the clinical signs of the affected animals (cough and fever).
Certainly, this could create a selection bias in the sample towards more
severe cases of respiratory disease in nurseries. To compensate for the
bias of selection based on swIAV suspicion we balanced swIAV-negative
and swIAV-positive cases. Moreover, although nasal swabs are optimal
samples for those viruses replicating in the nasal epithelium or in the
higher airways (such as swIAV or PCMV), its use can underestimate other
pathogens, such as PRRSV, in which replication in the nasal mucosa seems
to be related to virulence . This bias must be considered as well.
The results of the analysis of pooled nasal swabs indicated that IBV,
IDV, PPIV1 and PCV4 were not present in any of the outbreaks. Although
from these results it cannot be concluded that these viruses are absent
in Spanish pig herds, they suggest that, if present, their frequency is
low. This agrees with a previous report .
For the agents present, up to 33 combinations were found. Interestingly,
the presence of swIAV in the nurseries was associated with a higher
probability that the farm was positive to PRCV, SOV or PCMV. The causes
for that association are unknown. It can be speculated that maybe in
some farms, these associations reflected a poorer biosecurity or maybe
could be the result of a confounding variable. The fact that samples
were submitted for diagnosis with limited information makes it
impossible to further clarify this point. However, most often the
relationship between two different viruses that target the same organs
can result in interference. In the present case, when individual results
were examined, associations were of different nature.
Animals infected by swIAV were less likely to be infected with PRRSV.In vitro , co-infection of susceptible epithelial
CD163+ cells with PRRSV and swIAV resulted in
interference while, in pigs, some level of interference was observed
when PRRSV infection preceded swIAV inoculation . Interestingly, the
statistical analysis indicated that swIAV-positive animals were more
likely to be infected with PRCV. This result apparently contradicts
previous reports indicating that co-infection of swIAV and PRCV resulted
in lower viral replication and that prior in vitro infection with
swIAV strongly inhibits PRCV replication. In our case, PRCV infection
was associated with a lower probability of being infected by PRRSV or
PCMV. This observation would be consistent with the known induction of
type I interferon by PRCV and the known susceptibility of PRRSV and
cytomegaloviruses to interferons . SOV and PRCV seemed to be positively
associated. The confirmation of these associations would require either
a different epidemiological study or, if possible, an experimental
co-infection study.
Another interesting point to discuss is the different distribution of Ct
values between most pathogens and PCV2 and PCV3 (Figure 2). While for
the other agents (swIAV, PRRSV, SOV, PCMV), the most common finding in a
farm was that nasal swabs could contain either higher or lower viral
loads (as deduced from Ct values), most animals yielded Ct values above
30 for PCV2 and PCV3. This fact suggests that shedding of those viruses
was relatively low. In the case of PCV2, this is understandable since
all animals probably had high levels of maternally derived antibodies
and were vaccinated at weaning. For PCV3, the result is more difficult
to explain. found a higher prevalence of PCV3 in weaners with severe
respiratory disease indicating that Cts about 20-27 were common in
diseased animals, while Cts above 30 were found mostly in animals with
less severe respiratory disease or asymptomatic. This could be the case
in the present study.
Since for some farms we had samples from both suckling piglets and
nurseries, we examined the presence of four of the tested viruses (SOV,
PCV3, PRCV and PCMV) in those two compartments of the farm. The results
clearly indicated that all these agents started to circulate in the
farrowing units, suggesting the possibility of transmission from sows in
a pattern like in other diseases. For example, in the case of swIAV it
is well documented that in endemic farms transmission may start as early
as the first week of age .
In summary, the present study shows the complexity of the viruses
present in respiratory outbreaks of weaners and suggests the existence
of several interactions among them that deserve further study. Moreover,
we report here for the first time the presence of SOV in Spain.