Skip to main content
Download PDF

Changes in salivary biomarkers of stress, inflammation, redox status, and muscle damage due to Streptococcus suis infection in pigs

BMC Veterinary Research volume 19, Article number: 100 (2023) Cite this article

Abstract

Background

Streptococcus suis (S. suis) is a Gram-positive bacteria that infects pigs causing meningitis, arthritis, pneumonia, or endocarditis. This increases the mortality in pig farms deriving in severe economic losses. The use of saliva as a diagnostic fluid has various advantages compared to blood, especially in pigs. In this study, it was hypothesized that saliva could reflect changes in different biomarkers related to stress, inflammation, redox status, and muscle damage in pigs with S. suis infection and that changes in these biomarkers could be related to the severity of the disease.

Results

A total of 56 growing pigs from a farm were selected as infected pigs (n = 28) and healthy pigs (n = 28). Results showed increases in biomarkers related to stress (alpha-amylase and oxytocin), inflammation (haptoglobin, inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4), total protein, S100A8-A9 and S100A12), redox status (advanced oxidation protein producs (AOPP)) and muscle damage (creatine kinase (CK), CK-MB, troponin I, lactate, aspartate aminotransferase, and lactate dehydrogenase). An increase in adenosine deaminase (ADA), procalcitonin, and aldolase in infected animals were also observed, as previously described. The grade of severity of the disease indicated a significant positive correlation with total protein concentrations, aspartate aminotransferase, aldolase, and AOPP.

Conclusions

This report revealed that S. suis infection caused variations in analytes related to stress, inflammation, redox status, and muscle damage in the saliva of pigs and these can be considered potential biomarkers for this disease.

Peer Review reports

Background

The Gram-positive bacteria Streptococcus suis (S. suis) is one of the most frequent infectious diseases in pigs producing high mortality and major economic losses [1]. The most common lesions associated are meningitis, arthritis, pneumonia, or endocarditis [2]. This infection is also an important zoonosis, with the number of cases increasing in the last years, especially associated with the ingestion of uncooked pork and inadequate preventive barriers at slaughterhouses [3, 4].

Saliva contains analytes that can be used as biomarkers of various physiological pathways and reactions such as stress, inflammation, or sepsis [5]. It is also a non-invasive easy-to-collect sample that does not induce stress, making saliva a particularly interesting sample in pigs where blood collection is especially traumatic [5, 6], although it also can be used in other farm animals such as ruminants [7].

In a previous report, S. suis infection was shown to produce changes in the proteomic profile of saliva, due to activation of selected pathophysiological mechanisms leading to changes in selected analytes, e.g., an increase in adenosine deaminase (ADA), a marker of the immune system [8]. In addition, procalcitonin (PCT) and aldolase, biomarkers of sepsis, have been described to be increased in the saliva of pigs infected by S. suis [9]. These three analytes could be considered potential biomarkers for S. suis infection [9].

The hypothesis of this investigation is that in saliva of pigs infected with S. suis there could be changes in analytes other than those previously described (ADA, PCT, or aldolase) [8,9,10] and these analytes could be potential biomarkers of this disease. Therefore, the objective of this study was to evaluate the possible changes in different biomarkers of stress, inflammation, redox status, and muscle damage in pigs infected with S. suis. For this purpose, a comprehensive panel integrated by analytes that can reflect these different physiological pathways was measured. This panel consisted of cortisol, alpha-amylase (sAA), and oxytocin (OXT) as biomarkers of stress, haptoglobin (Hp), inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4, pig-MAP) and total proteins as indicators of inflammation, and the ferric-reducing ability of saliva (FRAS) and advanced oxidation protein products (AOPP) as biomarkers of redox status. Also, the S100A8-A9 (calprotectin, CALP) and S100A12 (calgranulin C), which are proteins related to inflammation and immunity [11] and also sepsis [12], were analyzed. In addition, creatine kinase (CK), CK-myocardial band (CK-MB), troponin I, lactate, lactate dehydrogenase (LDH), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were measured to assess possible muscle damage in the saliva of pigs with S. suis infection. These analytes were evaluated along with previously described biomarkers that are changed in S. suis infection, such as ADA, PCT, and aldolase [8,9,10].

Results

Changes of salivary analytes in pigs with meningitis by S. suis

The results (median and range) of the salivary biomarkers are presented in Table 1. In the group of biomarkers related to stress, sAA, cortisol, and oxytocin increased 9, 1.7, and 1.8-fold respectively in pigs with meningitis compared with healthy pigs. The biomarkers of inflammation haptoglobin and ITIH4 showed higher levels in pigs with meningitis than controls (1.5 and 1.6-fold, respectively). The total protein concentration also increased (1.9-fold) in pigs with meningitis with respect to healthy pigs. S100A8-A9 and S100A12 showed increases of 3.4 and 3.6-fold, respectively, in pigs with meningitis compared to healthy animals.

Table 1 Variations in the salivary biomarkers of pigs with meningitis (n = 28) compared with the healthy group (n = 28)
Full size table

Among the redox status markers, AOPP showed a significant increased of 1.5-fold in pigs with meningitis. In the case of muscle damage biomarkers, all of them showed higher levels in pigs with meningitis compared with healthy pigs: CK (1.3-fold), CK-MB (1.9-fold), troponin I (1.8-fold), lactate (3.27-fold), LDH (5.4-fold), AST (2.5-fold), and ALT (2.4-fold).

The immune system biomarker ADA increased 9.1-fold in the saliva of pigs with meningitis compared with controls. In addition, PCT and aldolase increased 3.3 and 1.6-fold, respectively, in pigs with meningitis compared with healthy pigs.

The ROC curve analyses showed AUCs higher than 0.8 (Table 2) for sAA (AUC = 0.96), total proteins (AUC = 0.92), S100A18/A9 (AUC = 0.89), S100A12 (AUC = 0.88), LDH (AUC = 0.87), PCT (AUC = 0.86), AST (AUC = 0.84), PCT (AUC = 0.86) and ADA (AUC = 0.92) (Table 3).

Table 2 Receiver operating characteristic (ROC) curve analysis for determination of cutoff value for the salivary analytes investigated in pigs with meningitis
Full size table

Correlation between analytes and the severity of the disease

The grade of severity of the disease showed a positive correlation with total protein (r = 0.75, p = 0.002), ALT (r = 0.62, p = 0.010), aldolase (r = 0.59, p = 0.040), and AOPP (r = 0.56, p = 0.040) values.

Discussion

The results of this report indicate that there is an increase in the values of several salivary analytes related to stress, inflammation, redox status, and muscle damage in pigs infected with S. suis infection. In this study, aldolase and PCT, as well as ADA, were higher in the saliva of pigs with the infection compared to healthy pigs. These results are in line with previous reports in which these analytes were shown to be increased in the saliva of pigs with meningitis due to S. suis infection [8,9,10] and corroborate that this disease produces changes in biomarkers of sepsis (PCT and aldolase) and immune system (ADA) in saliva.

In the group of analytes related to stress, cortisol, sAA and OXT were higher in pigs with meningitis than in healthy ones. No previous report was found about changes in cortisol in any species due to S. suis infection, however, in fish, Streptococcus iniae produces increases in this analyte [13]. In general, it has been described that infectious diseases increase cortisol, especially free cortisol [14]. In accordance, the measurement of cortisol in saliva could have the advantage of reflecting free cortisol in comparison with plasma [5]. sAA increases in immune-mediated diseases in humans such as systemic lupus erythematosus, possibly due to stress associated with the disease and the immune system activation [15]. The increase in this enzyme in our study could be associated with the pain induced by the disease, as described in other diseases in pigs that can produce an increase in stress markers because of the pain and discomfort [16]. OXT is a nonapeptide hormone used to assess positive and stressful situations in animals [17, 18]. However, few studies evaluated its relationship with sepsis, despite a relationship between OXT and sepsis or other inflammatory states has been suggested [19]. OXT has been shown to have anti-inflammatory effects [20] and a possible protective role against sepsis [21] by limiting organ damage associated with this pathology [19, 21]. Thus, the increase in OXT concentrations in pigs with meningitis found in this report, in comparison to healthy pigs, could reflect this role.

Among the analytes associated with inflammation, Hp, ITIH4, and total protein concentrations increased in pigs affected by S. suis. Hp was 1.5 -fold higher, which is consistent with the performance of haptoglobin as a moderate acute phase protein (APP) in swine [22, 23]. Increased Hp has been previously described in the serum of pigs with S. suis [8]. In addition, this APP was found to increase in inflammatory and infectious processes such as the administration of lipopolysaccharide from bacteria (LPS) [24] and viral infections [25]. Increases of ITIH4, also known as pig-MAP, in serum have been described in different inflammatory conditions in the pig [26]. The increments of total protein found in the saliva of pigs with meningitis found in this study could be due to the higher protein production in inflammation states; as it was observed in the serum of pigs with bacterial infections due to the increases in several APPs [27].

In this report, the oxidant AOPP increased 1.5-fold in the saliva of pigs affected by S. suis. In a recent study, increased concentrations of salivary AOPP were observed in pigs with experimentally induced sepsis, potentially attributed to the release of oxidant products during the sepsis process [28].

The muscle marker CK was also increased in the animals with the S. suis infection. Increases in CK and AST in serum have been observed during transportation, mainly associated with the physical activity that accompanies the handling that can cause muscle damage in the animals [29]. The main source of serum CK is skeletal muscle, whereas AST or ALT are less specific for skeletal muscle than CK because of its presence also in the liver [30]. Therefore, increases in AST and ALT could also indicate the possible presence of liver damage associated with meningitis.

Troponin I concentration and LDH activity were also increased in the saliva of pigs with meningitis. Troponins are considered high-specific cardiac alteration markers in humans [30] and different animal species such as sheep [31], being previously related to myocarditis associated with infection by Streptococcus [32] or meningitis [33]; whereas increases in LDH can be produced in addition to cardiac damage by the injury of other muscle types. The findings of this study would be in line with a previous report in which increases in salivary metavinculin (VCL), a cytoskeletal protein that anchors actin to the cell membrane present, among other tissues, in the cardiac muscle was described in S. suis infection in pigs [34]. In this regard, it was reported that the amelioration of LPS-induced sepsis caused a reduction of LDH [35] and troponins [36] due to the reduction of inflammation in the cardiac tissues. The presence of myocardial damage suggested by the increments in troponin I and LDH was also supported by the increments in CK-MB observed in the saliva of pigs with meningitis of our study. CK-MB is mostly found in the myocardium and is a diagnostic marker for myocardial damage caused by viral [37] and bacterial infections [38]. Overall, it could be hypothesized that meningitis in pigs caused disturbances in cardiac muscle and these changes can be observed in saliva.

S100A8-A9 and S100A12 are calcium-binding proteins of the S100 family, located in the cytosol of neutrophils and/or monocytes [39]. They are released after the activation of these cells, and they are involved in inflammation and sepsis having an antimicrobial function [40, 41]. In humans, serum S100A8-A9 is considered a marker of inflammation that can increase in conditions such as severe traumatic brain injury [11] and sepsis [42] and in saliva increased in immune-mediated diseases [43]. In pigs, S100A8-A9 in saliva was increased in sepsis and stressful situations [44]. It is interesting to point out that both proteins showed a significantly high correlation in this study (Spearman r = 0.90, p < 0.0001), similar to what has been described in the serum of humans where a Spearman r of 0.87 with a p < 0.0001 was found between S100A8-A9 and S100A12 in a study that includes septic and healthy individuals [45]. Further studies should elucidate the reason for the increase of these two proteins in pigs infected with S. suis.

sAA, total proteins, ADA, S100A8-A9, S100A12, LDH, PCT, and AST presented values of area under the curve (AUC) > 0.8 at receiving operating characteristics (ROC) curve analysis and therefore a good ability to distinguish between healthy pigs and pigs with S. suis infection. However, it should be stressed that in most cases there was an overlap of the values of the analytes between both groups and due to the non-specific nature of these markers, they cannot be diagnostics of the disease.

The grade of severity of diseased animals showed a positive correlation with some selected analytes, having the highest correlation with total proteins. Although further studies should be carried out to elucidate the reason behind this correlation, the higher severity of the diseased animals could reflect a higher inflammation associated with increases in this analyte.

It is important to point out, as was previously indicated above, that the analytes studied in this report cannot be used for the diagnosis of S. suis infection since specific methods for its detection are needed. However, they can potentially be useful for some practical applications already. For example, some of these analytes, such as the APPs, could be biomarkers of early detection to predict the possible presence of the disease in the near future in non-symptomatic animals. In addition, they could be useful for monitoring treatment efficacy. Also, the biomarkers of sepsis such as PCT and aldolase could help in order to detect if there is a need for antibiotic use, as occur in humans [46]. This would be in line with the new veterinary medicine regulation in the EU moving from in-feed antibiotic treatment to more targeted approaches like individual injectable antibiotics, which reduce their use. In addition, it would be of interest to study the possible measurement of these analytes in ropes, which can assess in a general way the status of the pigs in a pen and be of easier practical use.

There are some limitations in the study that should be stated. First, only male pigs were recruited, therefore the gender of the animals has not been considered and the effects of sex in the analytes evaluated could not be investigated. In addition, although, the statistical power obtained in this report was higher than 0.8, indicating that from a statistical point of view the number of animals included in this study was adequate, it would be interesting to evaluate larger populations and also different farms. In these studies, ROC analysis to evaluate the sensitivity and specificity of different analytes alone or in combination should be made. It would also be interesting to evaluate the potential of these analytes to distinguish pigs with meningitis from pigs with other diseases and not only with healthy animals. Also, these additional studies should explore the possible application of these markers to detect early infection and monitor the disease.

Conclusion

Overall, it can be concluded that the infection by S. suis produces changes in analytes related to sepsis such as PCT and aldolase, immune system such as ADA, stress such as sAA and OXT, inflammation such as Hp, ITIH4, total protein, S100A8-A9 and S100A12, redox status such as AOPP and muscle damage such as CK, CK-MB, AST, ALT, lactate, LDH, and troponin-I. These changes reflect that different pathophysiological mechanisms such as immune activation, stress, inflammation, oxidative disturbances or muscle damage are involved in this disease. In addition to provide information about the changes that occur in analytes in saliva in S. suis infection, this report opens the opportunity to further investigate these analytes as potential biomarkers of this disease in different situations such as early detection, prognosis or for monitoring response to treatment.

Methods

A total of 56 growing male pigs [(Sus scrofa domesticus) (Landrace × Large White)] from 6 to 9 weeks old from a commercial farm, were used in this study. Pigs were placed in pens containing a standard feeder and a nipple drinker to provide ad libitum access to feed and water with a minimum space of 0.65 m2 per animal (Council Directive 2001/88/CE of 23 October 2001 amending Directive 91/630/CEE concerning minimum standards for the protection of pigs) and an average temperature of 24 ± 2 °C. The pig commercial farm was selected based on the criteria of having a history of S. suis outbreaks.

The animals were classified into two different groups: (A) the healthy group (n = 28), integrated by clinically healthy pigs, and (B) the meningitis group (n = 28), composed of pigs diagnosed with meningitis induced by S. suis. The criteria to select the pigs of the meningitis group were: (1) having clinical signs compatible with S. suis infection, (2) not having been treated before, and (3) being positive for S. suis at the bacterial isolation and characterization. For this purpose, blood samples were incubated on Columbia blood agar plates (Oxoid Ltd., Madrid, Spain) supplemented with 5% defibrinated pig blood for 48 h at 37ºC under aerobic conditions [47]. The isolates were identified using standard procedures and confirmed by a polymerase chain reaction (PCR) based on the glutamate dehydrogenase gene, as previously described [8]. All animals of the meningitis group tested positive for S. suis serotype 9. The pigs were treated after diagnosis with injectable amoxicillin (Unicillin, Univet Ltd). The pig farms had no metaphylactic treatment in place at this time because they are looking for new approaches, in compliance with the new EU veterinary medicine regulation.

The severity of the disease was classified on a five-point scale [1- No clinical signs (control group), 2- mild, 3- moderate, 4- high, 5- severe disease] based on the presence of hyperthermia, arthritis, and two grades of neurological signs (Table 3). Pigs were clinically examined by the farm veterinarian before sample collection.

Table 3 Severity scale. - No presence; + Moderate; ++ Severe
Full size table

Sampling

Saliva was obtained using a sponge attached to a flexible thin metal rod as previously described [10]. Samples were stored in ice during sampling and transportation to the laboratory where they were centrifuged (3000 g, 10 min, 4 °C) to collect the supernatants and stored at -80 °C before biochemical analysis. Additionally, blood samples were obtained from a jugular vein after saliva collection to perform bacterial isolation. The animal study protocol was approved by the Ethical Committee on Animal Experimentation (CEEA) of the University of Murcia (CEEA 563/2019).

Biochemical analysis of saliva

Biomarkers of stress

Cortisol and OXT concentrations were measured by two amplified luminescent proximity homogeneous (AlphaLisa) assays previously validated in pig saliva samples [48, 49]. The sAA activity was measured by a commercial assay (a-Amylase, OSR6182, Beckman Coulter) previously validated in porcine saliva [50] in an Olympus AU400 autoanalyzer (Beckman Olympus AU400 Chemistry Analyzer, Beckman Coulter).

Biomarkers of inflammation

Hp concentration was measured by an assay based on AlphaLisa technology previously used in pig saliva [51]. ITIH4 was measured using a porcine species-specific commercially available ELISA kit (Porcine ITIH4, ElabSciences). The kit showed values of intra and inter-imprecision lower than 15% and accurate results in linearity under dilution for quantifying the ITIH4 in the saliva of pigs. Total protein concentration was analyzed using a colorimetric kit to measure Low-Complexity Region (LCR) proteins (protein in urine and CSF, Spinreact). S100A8-A9 was analyzed with a commercially available immunoturbidimetric assay (BÜHLMANN fCal Turbo® assay, Laboratories AG) using an Olympus AU400 autoanalyzer. This assay is designed for humans, but it has been demonstrated to have cross-reactivity with CALPS100A8-A9 in pigs [38] and it has been validated in the saliva of this species [44]. SA100A12 was measured with the SEB080Po Cloud-Clone ELISA kit, which is a specific assay for the measurement of this protein in pigs. This assay provided an intra and inter-assay imprecision lower then 15% and was linear after serial sample dilutions.

Biomarkers of redox status

FRAS was determined by the reduction of ferric-tripyridyltriazine (Fe3+-TPTZ, Sigma-Aldrich Co.) to the ferrous (Fe2+) form [52] and the AOPP based on a method previously described [53] and both were previously used in pig saliva [51]. These analyses were carried out using an Olympus AU400 autoanalyzer.

Biomarkers of muscle damage

CK, CK-MB, AST, ALT, and lactate were measured using commercial kits from Beckman (Beckman Coulter Inc., Fullerton, CA, USA) while LDH was a commercial kit from Biosystem (Biosystem S.A., Barcelona, Spain) that was previously validated in the saliva of pigs [54]. These methods were performed using an Olympus AU400 autoanalyzer. Troponin I was quantified by a solid-phase enzyme-labeled chemiluminescent immunometric assay (IMMULITE Troponins I, Siemens Medical Solutions Diagnostics) in an IMMULITE 1000 immunoassay system.

CK, AST, ALT, LDH, lactate, and troponin I provided an intra- and inter-assay imprecision of < 15% and accurate results in linearity under dilution assays. In the case of troponin I determinations, values lower than the low limit of analytical detection of 0.2 ng/mL were established as 0.2 ng/mL.

Biomarkers of the immune system

ADA was analyzed with a commercially available spectrophotometric automated assay (Adenosine Deaminase assay kit, Diazyme Laboratories), previously validated for porcine saliva [55].

Biomarkers of sepsis

PCT was measured using an in-house indirect competitive AlphaLisa previously validated [10] and aldolase through a commercially available reagent kit (Aldolase, Randox Laboratories Ltd., Crumlin, UK) in an Olympus AU400 autoanalyzer.

Statistical analysis

Data were assessed for normality by the Shapiro-Wilk method and showed non-normal distribution. A non-parametric approach was followed to analyze all the results. Mann-Whitney test was used to compare the differences in each variable between groups. Results were expressed as median and range. ROC curve was calculated for each variable to determine the cut-off that distinguished between groups. Those analytes showing a significant AUC were selected to calculate the cut-off values according to a protocol previously published [56]. A correlation study between the severity of the disease and the different analytes evaluated was performed through the Spearman test for non-parametric data. Results were considered significant when p < 0.05. The statistical analysis was performed using GraphPad Prism 9 software for Mac (GraphPad Software, LLC, San Diego, CA, USA). The statistical power of the results (1 – β) was calculated by a posthoc analysis by the G-Power program (Dusseldorf, Germany).

Data Availability

Not applicable.

Abbreviations

S. suis:

Streptoccocus suis

CK:

Creatine kinase

CK-MB:

Creatine kinase myocardial band

LDH:

Lactate dehydrogenase

ADA:

Adenosine deaminase

PCT:

Procalcitonin

SAA:

Alpha-amylase

OXT:

Oxytocin

AOPP:

Advanced oxidation protein products

AST:

Aspartate aminotransferase

ALT:

Alanine aminotransferase

CALP:

Calprotectin

FRAS:

Ferric reducing ability of saliva

LPS:

Lipopolysaccharide

AUC:

Area under the curve

ROC:

Receiving operating characteristics

EU:

European Union

PCR:

Polymerase chain reaction

CEEA:

Ethical Committee on Animal Experimentation

LCR:

Low-Complexity Region

ITIH4:

Inter-alpha trypsin inhibitor 4

References

  1. Madsen LW, Svensmark B, Elvestad K, Aalbaek B, Jensen HE. Streptococcus suis serotype 2 infection in pigs: new diagnostic and pathogenetic aspects. J Comp Pathol. 2002;126:57–65.

    Article  CAS  PubMed  Google Scholar 

  2. Fittipaldi N, Segura M, Grenier D, Gottschalk M. Virulence factors involved in the pathogenesis of the infection caused by the swine pathogen and zoonotic agent Streptococcus suis. Future Microbiol. 2012;7:259–79.

    Article  CAS  PubMed  Google Scholar 

  3. Feng Y, Zhang H, Wu Z, Wang S, Cao M, Hu D, et al. Streptococcus suis infection: an emerging/reemerging challenge of bacterial infectious diseases? Virulence. 2014;5:477–97.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Wertheim HFL, Nghia HDT, Taylor W, Schultsz C. Streptococcus suis: an emerging human pathogen. Clin Infect Dis. 2009;48:617–25.

    Article  PubMed  Google Scholar 

  5. Cerón JJ, Contreras-Aguilar MD, Escribano D, Martínez-Miró S, López-Martínez MJ, Ortín-Bustillo A, et al. Basics for the potential use of saliva to evaluate stress, inflammation, immune system, and redox homeostasis in pigs. BMC Vet Res. 2022;18:81.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Wolf TE, Mangwiro N, Fasina FO, Ganswindt A. Non-invasive monitoring of adrenocortical function in female domestic pigs using saliva and faeces as sample matrices. PLoS ONE. 2020;15:e0234971.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Cabassi E, Miduri F, Di Lecce R, Marin A, Ferri L, Corradi A. Saliva, an alternative Biologic Matrix to detect glucocorticoid treatment in calves: experimental contribution. Vet Res Commun. 2007;31:217–20.

    Article  PubMed  Google Scholar 

  8. López-Martínez MJ, Beletić A, Kuleš J, Rešetar-Maslov D, Rubić I, Mrljak V, et al. Revealing the changes in saliva and serum proteins of Pigs with Meningitis caused by Streptococcus Suis: a Proteomic Approach. Int J Mol Sci. 2022;23:13700.

    Article  PubMed  PubMed Central  Google Scholar 

  9. López-Martínez MJ, Cerón JJ, Ortín-Bustillo A, Escribano D, Kuleš J, Beletić A, et al. A Proteomic Approach to elucidate the changes in saliva and serum proteins of Pigs with septic and non-septic inflammation. Int J Mol Sci. 2022;23:6738.

    Article  PubMed  PubMed Central  Google Scholar 

  10. López-Martínez MJ, Escribano D, Martínez-Miró S, Ramis G, Manzanilla EG, Tecles F, et al. Measurement of procalcitonin in saliva of pigs: a pilot study. BMC Vet Res. 2022;18:139.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Yang Y, Shen L, Xu M, Chen L, Lu W, Wang W. Serum calprotectin as a prognostic predictor in severe traumatic brain injury. Clin Chim Acta. 2021;520:101–7.

    Article  CAS  PubMed  Google Scholar 

  12. Chen H, Li C, Fang M, Zhu M, Li X, Zhou R, et al. Understanding Haemophilus parasuis infection in porcine spleen through a transcriptomics approach. BMC Genomics. 2009;10:64.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Qiang J, He J, Yang H, Xu P, Habte-Tsion HM, Ma XY, et al. The changes in cortisol and expression of immune genes of GIFT tilapia Oreochromis niloticus (L.) at different rearing densities under Streptococcus iniae infection. Aquacult Int. 2016;24:1365–78.

    Article  CAS  Google Scholar 

  14. Torpy D, Ho J. Value of free cortisol measurement in systemic infection. Horm Metab Res. 2007;39:439–44.

    Article  CAS  PubMed  Google Scholar 

  15. Jung J-Y, Nam J-Y, Kim H-A, Suh C-H. Elevated salivary alpha-amylase level, Association between Depression and Disease Activity, and stress as a predictor of Disease Flare in systemic Lupus Erythematosus. Medicine. 2015;94:e1184.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Contreras-Aguilar MD, Escribano D, Martínez-Miró S, López-Arjona M, Rubio CP, Martínez-Subiela S, et al. Application of a score for evaluation of pain, distress and discomfort in pigs with lameness and prolapses: correlation with saliva biomarkers and severity of the disease. Res Vet Sci. 2019;126:155–63.

    Article  CAS  PubMed  Google Scholar 

  17. López-Arjona M, Padilla L, Roca J, Cerón JJ, Martínez-Subiela S. Ejaculate Collection Influences the salivary oxytocin concentrations in breeding male Pigs. Animals. 2020;10:1268.

    Article  PubMed  PubMed Central  Google Scholar 

  18. López-Arjona M, Escribano D, Mateo S, Contreras-Aguilar MD, Rubio CP, Tecles F, et al. Changes in oxytocin concentrations in saliva of pigs after a transport and during lairage at slaughterhouse. Res Vet Sci. 2020;133:26–30.

    Article  PubMed  Google Scholar 

  19. Sendemir E, Kafa IM, Schäfer HH, Jirikowski GF. Altered oxytocinergic hypothalamus systems in sepsis. J Chem Neuroanat. 2013;52:44–8.

    Article  CAS  PubMed  Google Scholar 

  20. Mehdi SF, Pusapati S, Khenhrani RR, Farooqi MS, Sarwar S, Alnasarat A et al. Oxytocin and related peptide hormones: candidate anti-inflammatory therapy in early stages of Sepsis. Front Immunol. 2022;13.

  21. İşeri S, Şener G, Saǧlam B, Gedik N, Ercan F, Yeǧen B. Oxytocin protects against Sepsis-Induced multiple organ damage: role of neutrophils. J Surg Res. 2005;126:73–81.

    Article  PubMed  Google Scholar 

  22. Cerón JJ, Tecles F, Escribano D, Fuentes-Pardo P, Martínez-Subiela S. Acute phase proteins in pigs: from theory to practice. Suis. 2016;127.

  23. López-Martínez MJ, Franco-Martínez L, Martínez-Subiela S, Cerón JJ. Biomarkers of sepsis in pigs, horses and cattle: from acute phase proteins to procalcitonin. Anim Health Res Rev. 2022;23:82–99.

    Article  PubMed  Google Scholar 

  24. Yin C, Liu W, Liu Z, Huang Y, Ci L, Zhao R, et al. Identification of potential serum biomarkers in pigs at early stage after Lipopolysaccharide injection. Res Vet Sci. 2017;111:140–6.

    Article  PubMed  Google Scholar 

  25. Gomez-Laguna J, Gutierrez A, Pallares FJ, Salguero FJ, Ceron JJ, Carrasco L. Haptoglobin and C-reactive protein as biomarkers in the serum, saliva and meat juice of pigs experimentally infected with porcine reproductive and respiratory syndrome virus. Vet J. 2010;185:83–7.

    Article  CAS  PubMed  Google Scholar 

  26. Parra MD, Fuentes P, Tecles F, Martínez-Subiela S, Martínez JS, Muñoz A, et al. Porcine Acute phase protein concentrations in different Diseases in Field Conditions. J Vet Med Ser B. 2006;53:488–93.

    Article  CAS  Google Scholar 

  27. Heegaard PMH, Klausen J, Nielsen JP, González-Ramón N, Piñeiro M, Lampreave F et al. The Porcine Acute Phase response to infection with Actinobacillus pleuropneumoniae. Haptoglobin, C-Reactive protein, Major Acute phase protein and serum amyloid A protein are sensitive indicators of infection. 1998.

  28. López-Martínez MJ, Escribano D, Ortín-Bustillo A, Franco-Martínez L, González-Arostegui LG, Cerón JJ et al. Changes in biomarkers of Redox Status in Saliva of Pigs after an experimental Sepsis induction. Antioxidants. 2022;11.

  29. Golightly HR, Brown J, Bergeron R, Poljak Z, Roy RC, Seddon YM et al. Physiological response of weaned piglets to two transport durations observed in a canadian commercial setting. J Anim Sci. 2021;99.

  30. Brancaccio P, Lippi G, Maffulli N. Biochemical markers of muscular damage. Clin Chem Lab Med. 2010;48:757–67.

    Article  CAS  PubMed  Google Scholar 

  31. Aslani MR, Mohri M, Movassaghi AR. Serum troponin I as an indicator of myocarditis in lambs affected with foot and mouth disease. Vet Res Forum. 2013;4:59–62.

    PubMed  PubMed Central  Google Scholar 

  32. Allen J, Munoz C, Byakova A, Pachulski R. Acute fulminant group A beta-hemolytic Streptococcus-associated carditis: a case report and literature review. Cureus. 2022;14(7):e27282.

  33. Varghese M, Alsoub HARS, Koleri J, el Ajez RHM, Alsehli ZM, Alkailani YIG et al. Multisystem inflammatory syndrome in children (MIS-C) secondary to COVID-19 mRNA vaccination – a case report from Qatar. IDCases. 2022;30.

  34. Lee HT, Sharek L, Timothy O’Brien E, Urbina FL, Gupton SL, Superfine R, et al. Vinculin and metavinculin exhibit distinct effects on focal adhesion properties, cell migration, and mechanotransduction. PLoS ONE. 2019;14:1–20.

    Google Scholar 

  35. Jiao Y, Zhang Q, Zhang J, Zha Y, Wang J, Li Y et al. Platelet-rich plasma ameliorates lipopolysaccharide-induced cardiac injury by inflammation and ferroptosis regulation. Front Pharmacol. 2022;13.

  36. Fu W, Fang X, Wu L, Hu W, Yang T. Neogambogic acid relieves myocardial injury induced by sepsis via p38 MAPK/NF-κB pathway. Korean J Physiol Pharmacol. 2022;26:511–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Cersosimo A, Cimino G, Amore L, Calvi E, Pascariello G, Inciardi RM, et al. Cardiac biomarkers and mortality in COVID-19 infection: a review. Monaldi Arch Chest Dis. 2022;93(1).

  38. Lai M, Ai T, Yang S, Wei Y, Deng Y, Yu X, et al. The value of high-sensitivity C-reactive protein in evaluating myocardial damage and the prognosis in children with Mycoplasmal Pneumonia. Ann Clin Lab Sci. 2021;51:721–5.

    CAS  PubMed  Google Scholar 

  39. Cerón JJ, Ortín-Bustillo A, José López-Martínez M, Martínez-Subiela S, David Eckersall P, Tecles F et al. S-100 proteins: basics and applications as biomarkers in animals with special focus on calgranulins (S100A8, A9, and A12). Biology (Basel). 2023;12.

  40. Barbosa JA, Rodrigues LA, Columbus DA, Aguirre JCP, Harding JCS, Cantarelli VS et al. Experimental infectious challenge in pigs leads to elevated fecal calprotectin levels following colitis, but not enteritis. Porcine Health Manag. 2021;7.

  41. Bartáková E, Štefan M, Stráníková A, Pospíšilová L, Arientová S, Beran O, et al. Calprotectin and calgranulin C serum levels in bacterial sepsis. Diagn Microbiol Infect Dis. 2019;93:219–26.

    Article  PubMed  Google Scholar 

  42. Larsson A, Tydén J, Johansson J, Lipcsey M, Bergquist M, Kultima K, et al. Calprotectin is superior to procalcitonin as a sepsis marker and predictor of 30-day mortality in intensive care patients. Scand J Clin Lab Invest. 2020;80:156–61.

    Article  CAS  PubMed  Google Scholar 

  43. Kim JW, Jung JY, Lee SW, Baek WY, Kim HA, Suh CH. S100A8 in serum, urine, and Saliva as a potential biomarker for systemic Lupus Erythematosus. Front Immunol. 2022;13.

  44. López-Martínez MJ, Martínez-Subiela S, Cerón JJ, Ortín-Bustillo A, Ramis G, López-Arjona M, et al. Measurement of calprotectin (S100A8/A9) in the Saliva of Pigs: Validation Data of a commercially available automated assay and changes in Sepsis, inflammation, and stress. Animals. 2023;13:1190.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Dubois C, Marcé D, Faivre V, Lukaszewicz A-C, Junot C, Fenaille F, et al. High plasma level of S100A8/S100A9 and S100A12 at admission indicates a higher risk of death in septic shock patients. Sci Rep. 2019;9:15660.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Liu HH, Guo JB, Geng Y, Su L. Procalcitonin: present and future. Ir J Med Sci. 2015;184:597–605. (1971 -).

    Article  CAS  PubMed  Google Scholar 

  47. Petrocchi-Rilo M, Martínez-Martínez S, Aguarón-Turrientes Á, Roca-Martínez E, García-Iglesias M-J, Pérez-Fernández E, et al. Anatomical site, typing, virulence gene profiling, Antimicrobial susceptibility and resistance genes of Streptococcus suis isolates recovered from Pigs in Spain. Antibiotics. 2021;10:707.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. López-Arjona M, Tecles F, Mateo SV, Contreras-Aguilar MD, Martínez-Miró S, Cerón JJ, et al. Measurement of cortisol, cortisone and 11β-hydroxysteroid dehydrogenase type 2 activity in hair of sows during different phases of the reproductive cycle. Vet J. 2020;259–260:105458.

    Article  PubMed  Google Scholar 

  49. López-Arjona M, Mateo SV, Manteca X, Escribano D, Cerón JJ, Martínez-Subiela S. Oxytocin in saliva of pigs: an assay for its measurement and changes after farrowing. Domest Anim Endocrinol. 2020;70:106384.

    Article  PubMed  Google Scholar 

  50. Fuentes M, Tecles F, Gutiérrez A, Otal J, Martínez-Subiela S, Cerón JJ. Validation of an automated method for salivary alpha-amylase measurements in Pigs (Sus Scrofa Domesticus) and its application as a stress biomarker. J Vet Diagn Invest. 2011;23:282–7.

    Article  PubMed  Google Scholar 

  51. Contreras-Aguilar MD, Escribano D, Martínez-Subiela S, Martín-Cuervo M, Lamy E, Tecles F, et al. Changes in saliva analytes in equine acute abdominal disease: a sialochemistry approach. BMC Vet Res. 2019;15:187.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Benzie IFF, Strain JJ. The Ferric reducing ability of plasma (FRAP) as a measure of “Antioxidant Power”: the FRAP Assay. Anal Biochem. 1996;239:70–6.

    Article  CAS  PubMed  Google Scholar 

  53. Witko-Sarsat V, Friedlander M, Capeillère-Blandin C, Nguyen-Khoa T, Nguyen AT, Zingraff J, et al. Advanced oxidation protein products as a novel marker of oxidative stress in uremia. Kidney Int. 1996;49:1304–13.

    Article  CAS  PubMed  Google Scholar 

  54. Escribano D, Horvatić A, Contreras-Aguilar MD, Guillemin N, Cerón JJ, Tecles F, et al. Changes in saliva proteins in two conditions of compromised welfare in pigs: an experimental induced stress by nose snaring and lameness. Res Vet Sci. 2019;125:227–34.

    Article  CAS  PubMed  Google Scholar 

  55. Tecles F, Rubio CP, Contreras-Aguilar MD, Lopez-Arjona M, Martinez-Miro S, Martinez-Subiela S, et al. Adenosine deaminase activity in pig saliva: analytical validation of two spectrophotometric assays. J Vet Diagn Invest. 2018;30:175–9.

    Article  CAS  PubMed  Google Scholar 

  56. Perkins NJ, Schisterman EF. The inconsistency of “Optimal” Cutpoints obtained using two Criteria based on the receiver operating characteristic curve. Am J Epidemiol. 2006;163:670–5.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This study was supported by a Grant Reference PID2019-105950RB-100 funded by MCIN/AEI/10.13039/501100011033. It was also supported by a Grant Reference PCI2020-120712-2 from MCIN/AEI/10.13039/501100011033 and European Union “NextGenerationEU”/PRTR (1st ICRAD Joint Cofund Call). M.J.L-M. was funded by 21293/FPI/19, Fundación Séneca, Región de Murcia (Spain). D.E. was funded by the postdoctoral contract “Generational renewal to promote research” of the University of Murcia. M.L-A. has a postdoctoral fellowship “Juan de la Cierva Formación” supported by the Ministerio de Ciencia e Innovación (FJC2021-047105-I). A.M-P. T has a post-doctoral fellowship “Ramón y Cajal” supported by the Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación (AEI), Spain, and The European Next Generation Funds (NextgenerationEU) (RYC2021-033660-I).

Author information

Authors and Affiliations

  1. Interdisciplinary Laboratory of Clinical Analysis (Interlab-UMU), Regional Campus of International Excellence ‘Campus Mare Nostrum, University of Murcia, Espinardo, Murcia, 30100, Spain

    María José López-Martínez, Silvia Martínez-Subiela, Fernando Tecles, Asta Tvarijonaviciute, Damián Escribano, José Joaquín Cerón, Marina López-Arjona & Alberto Muñoz-Prieto

  2. Pig Development Department, The Irish Food and Agriculture Authority, Teagasc, Moorepark, Fermoy, Co Cork, P61 C996, Ireland

    Mario Andre S. Ornelas & Edgar Garcia Manzanilla

  3. School of Veterinary Medicine, University College Dublin, Belfield, Dublin, Ireland

    Mario Andre S. Ornelas & Edgar Garcia Manzanilla

  4. Department of Agriculture, Food, and Environment, University of Pisa, Pisa, Italy

    Roxana Elena Amarie

  5. Departamento de Producción y Sanidad Animal, Facultad de Veterinaria, Universidad Cardenal Herrera-CEU, CEU Universities, C/Tirant lo Blanc, 7, Alfara del Patriarca, Valencia, 46115, Spain

    Antonio González-Bulnes

Authors
  1. María José López-Martínez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mario Andre S. Ornelas
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Roxana Elena Amarie
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Edgar Garcia Manzanilla
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Silvia Martínez-Subiela
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Fernando Tecles
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Asta Tvarijonaviciute
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Damián Escribano
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Antonio González-Bulnes
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. José Joaquín Cerón
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Marina López-Arjona
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Alberto Muñoz-Prieto
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: E.G.M., J.J.C., M.L-A., and A.M-P.Methodology, M.J.L-M., J.J.C., and A.M-P.Software, M.J.L-M., and A.M-P.Validation, M.J.L-M., J.J.C., and A.M-P.Formal analysis, M.J.L-M., S.M-S., F.T, and A.M-P.Investigation, M.J.L-M., E.G.M., A.T., D.E., J.J.C., and A.M-P.Resources, E.G.M., S.M-S., F.T., A.T., and J.J.C.Data curation, M.J.L-M., J.J.C., and A.M-P.Writing—original draft preparation, M.J.L-M., J.J.C., and A.M-P. Writing—review and editing, M.J.L-M., M.A.S.O., R.E.A., E.G.M., S.M-S., F.T., A.T., D.E., A.G-B., J.J.C., M.L-A., and A.M-P.Visualization, E.G.M., S.M-S., F.T., A.T., A.G-B., and J.J.C.Supervision, J.J.C., and A.M-P.Project administration, E.G.M., and J.J.C.Funding acquisition, J.J.C., and A.M-P. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Alberto Muñoz-Prieto.

Ethics declarations

Ethics approval and consent to participate

The animal study protocol was approved by the Ethical Committee on Animal Experimentation (CEEA) of the University of Murcia (A13220196; approval date: 4 March 2021) according to the European Council Directives considering the protection of animals used for experimental purposes. In addition, this study complies with Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines for the care and use of animals.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

López-Martínez, M.J., Ornelas, M.A.S., Amarie, R.E. et al. Changes in salivary biomarkers of stress, inflammation, redox status, and muscle damage due to Streptococcus suis infection in pigs. BMC Vet Res 19, 100 (2023). https://doi.org/10.1186/s12917-023-03650-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12917-023-03650-z

Keywords

BMC Veterinary Research

ISSN: 1746-6148

Contact us