The study was conducted at veterinary clinics in the city of Kostanay, as well as at the Laboratory of Clinical, Diagnostic and Microbiological Research and the Laboratory of Molecular and Genetic Analysis of the Research Institute of Applied Biotechnology at the Akhmet Baitursynov Kostanay Regional University, Kostanay, Republic of Kazakhstan.

To assess the epizootic spread of parvovirus infection among dogs between January 2020 and December 2024, 549 dogs of various breeds, aged between 1 month and 1 year, with clinical symptoms of gastrointestinal disease, were examined. A total of 198 dogs were diagnosed with parvovirus enteritis.

To diagnose parvovirus enteritis, the following evaluation was performed: collection of the medical history of the animal (age, sex, dietary habits, and vaccination and deworming status) and the disease (nature of the disease, whether the animal had been ill before and whether it had been treated with antibacterial drugs); physical examination for the presence of pathognomonic symptoms of the disease (apathy, refusal to eat, vomiting, diarrhoea, hyperthermia, and dehydration); and laboratory tests (morphological and biochemical blood tests). In addition, an ultrasound examination was performed. The final diagnosis of dogs suspected of having parvovirus enteritis was established on the basis of a comprehensive diagnostic approach that included immunochromatographic analysis to detect CPV-2 antigens (CPV-2/2a/2b/2c) in faecal samples, as well as confirmatory polymerase chain reaction (PCR) with viral DNA detection. The use of two complementary techniques improved the diagnostic accuracy and minimized the risk of false negative results in the early stages of infection.

CPV-2 was diagnosed using real-time polymerase chain reaction (real-time PCR).

Before extraction, the faecal samples were thoroughly homogenized in saline solution to obtain a 10% suspension. After a brief settling period, the supernatant was used for DNA extraction. When a rectal swab was used, the swab was transferred to 500 μL of a physiological solution and centrifuged to precipitate the particles.

For molecular detection, a conserved region of the VP2 structural gene characteristic of canine parvovirus type 2 (CPV-2) was used.

The following primers, selected on the basis of published diagnostic protocols (22, 23), were used for CPV-2 DNA amplification:

Target region: VP2 gene fragment; amplicon length: 583 bp.

A 25 μL reaction mixture was prepared according to the test system manufacturer’s instructions and included 5 μL of isolated DNA.

Amplification method:

Positive, negative and internal controls were used in each reaction to confirm the validity of the results. The analytical sensitivity of the test system was at least 10³ genome equivalents/ml.

Haematological analyses were performed using an Exigo 17 veterinary haematology analyser (Spånga, Sweden), and 18 parameters were measured. Biochemical analyses were conducted in a BioChem FC-120 automated biochemical analyser (High Technology Inc., North Attleborough, MA, USA), which assessed 18 parameters, including potassium, phosphorus, sodium, urea, and creatinine. The reference ranges automatically established by each analyser were used as the standard values for blood parameters.

To assess the impact of parvovirus infection on the frequency of carriage and shedding of opportunistic microorganisms, two comparable groups of dogs were included in the study:

Exclusion criteria: antibacterial/antifungal therapy within 30 days; severe stomatitis/rhinitis/diarrhoea (for enrolment in Group 2); intake of probiotics ≥10⁹ CFU/day in the past 7 days; and owner refusal.

Before admission to the hospital, clinical swabs were collected from all the dogs immediately upon initial entry, before placement in the reception area or treatment room. Samples were collected under aseptic conditions using standard sterile swabs. Biomaterial (from the oral cavity/gums, oropharynx, nasopharynx, and rectum) was collected for the isolation and identification of opportunistic microorganisms using a sterile swab, which was pressed firmly against the mucous membrane and rotated evenly for 5–10 s. The time from sampling to culture was ≤4 h. Negative control samples and standardized culture methods were used to control for contamination. If the phenotypic characteristics of bacteria isolated from clinical samples matched those of isolates from the clinic environment, we performed molecular typing to confirm their genetic relationship.

Pure cultures of microorganisms were isolated and grown using universal chromogenic and differential diagnostic culture media. Species identification of the isolates was performed using a MALDI Biotyper sirius RUO microbiological analyser.

The initial growth of microorganisms was carried out by seeding the material in meat peptone broth (MPB) prior to incubation at 36–37 °C for 18–24 h. Afterwards, the material was transferred to universal and chromogenic differential diagnostic culture media (including CHROMagar™ for enterobacteria and staphylococci) and incubated at 36–37 °C for 18–24 h. After the appearance of characteristic colonies, macroscopic evaluation of growth (colour, shape, size, haemolysis, and surface characteristics) and microscopy of Gram-stained smears were performed for preliminary differentiation of gram-positive and gram-negative bacteria.

Pure cultures were obtained by repeated subculturing of isolated typical colonies and incubation under the same conditions until single-strain growth was accomplished. Species identification of Escherichia coli, Klebsiella spp. and Staphylococcus aureus was performed using the MALDI Biotyper sirius RUO microbiological analyser (Bruker, Germany) in accordance with the manufacturer’s instructions.

The antimicrobial sensitivity of isolated bacterial strains of E. coli, Klebsiella spp., and S. aureus was assessed using the disc diffusion method (Kirby–Bauer) on Mueller–Hinton agar in accordance with the recommendations of the Clinical and Laboratory Standards Institute (CLSI) (24). A standardized bacterial suspension was prepared to a density of 0.5 on the McFarland scale, after which it was evenly applied to the surface of agar plates with a sterile swab. The plates were incubated at 35–37 °C for 18–24 h; then, the sensitivity model was evaluated by measuring the diameter of the inhibition zone, and the isolates were considered resistant, intermediate, or susceptible according to the CLSI ranges (24). The E. coli ATCC 25922 and S. aureus ATCC 25923 reference strains were used to control the quality of the media used and the correctness of the test setup.

For testing of microorganisms of the Enterobacteriaceae family, a panel of 17 antibiotics was used: amoxicillin, 25 μg; ampicillin, 10 μg; cefoperazone, 75 μg; cefoxitin, 30 μg; cefpodoxime, 10 μg; meropenem, 10 μg; streptomycin, 10 μg; kanamycin, 30 μg; gentamicin, 10 μg; tetracycline, 15 μg; doxycycline, 30 μg; enrofloxacin, 5 μg; ciprofloxacin, 5 μg; norfloxacin, 10 μg; ofloxacin, 5 μg; gemifloxacin, 5 μg; and sulfamethoxazole/trimethoprim, 23.75 μg/1.25 μg. For testing of S. aureus, a panel of 16 antibiotics was used: amoxicillin, 25 μg; ampicillin, 10 μg; penicillin, 10 μg; cefoperazone, 75 μg; cefoxitin, 30 μg; streptomycin, 10 μg; kanamycin, 30 μg; neomycin, 30 μg; gentamicin, 10 μg; tetracycline, 30 μg; doxycycline, 30 μg; erythromycin, 15mcg; tylosin, 15mcg; sulfamethoxazole/trimethoprim, 23.75 mcg/1.25 mcg; ciprofloxacin, 5 mcg; and norfloxacin, 10 mcg.

To prevent contamination and cross-contamination of samples, the principle of unidirectional laboratory flow was strictly observed: the processes of sample reception and registration, seeding, incubation and identification were carried out in separate areas. All manipulations were carried out under aseptic conditions using disposable sterile consumables (swabs, loops, and filter tips), which were replaced for each new sample. The work surfaces were treated with disinfectant solutions before and after work and were also subjected to ultraviolet irradiation in accordance with laboratory regulations.

Genomic DNA from phenotypically identified microbial colonies was extracted by the boiling method using PureLink Genomic DNA Kits (Thermo Fisher Scientific, USA) according to the manufacturer’s instructions and was then stored at −20 °C until further analysis. For genotypic analysis of the strains, genes associated with resistance to β-lactam antibiotics (blaTEM, OXA, blaZ, mecA), aminoglycosides (strA, strB, aadB, aphA1, aac(6′)-aph(2″), and aph(3′)), tetracyclines (tetA, tetB, tetK, and tetM), sulfonamides (sul1 and sul3), trimethoprim (dfrG and dfrK), fluoroquinolones (qepA and qnr), and macrolides (ermC and ermB) were targeted. Primers were selected considering the antibiotic and antimicrobial classes most commonly used in veterinary practice (Table 1). The synthesis of primers and fluorescently labelled probes was performed at the National Center for Biotechnology (Astana, Kazakhstan; Z05K8A3).

To identify toxin-producing E. coli, 24-h cultures of the microorganisms were streaked onto the chromogenic media CHROMagar™ STEC and CHROMagar™ O157 (CHROMagar, France) for the detection of Shiga toxin-producing E. coli (STEC) and for the qualitative identification of E. coli serotype O157: H7. The plates were incubated for 18–24 h at 37 °C, after which the colonies were examined and identified.

For the detection of Staphylococcus aureus enterotoxins in bacterial cultures, a commercial enzyme-linked immunosorbent assay (ELISA) kit for the combined detection of enterotoxins A–E (RIDASCREEN^® SET Total, R-Biopharm AG, Germany) was used.

S. aureus isolates obtained on selective media were identified according to standard microbiological criteria and were then precultured in brain heart infusion (BHI) broth to optimize enterotoxin production. A cell suspension was subsequently prepared following the manufacturer’s instructions, and culture supernatants were used for analysis.

Samples and control solutions were added to wells precoated with specific antibodies against enterotoxins A–E. Incubation was performed according to the kit protocol. After the samples were washed, the antibody conjugate was added, after which the chromogenic substrate was added. The reaction was stopped by the addition of stop solution, and the optical density (OD) was measured at 450 nm using an ELISA reader. A positive result was defined according to the manufacturer’s criteria: the sample OD value exceeded the threshold calculated from the negative control.

Using this ELISA kit, enterotoxins SEA, SEB, SEC, SED, and SEE were simultaneously detected in culture supernatants of S. aureus isolates obtained from dogs in both study groups.

The study power was calculated to compare two independent groups with an expected difference in the frequency of bacterial coinfection of at least 15% at a significance level of α = 0.05 and a statistical power of 80%. On the basis of the calculation, the minimum required sample size per group was ≥180 animals.

Descriptive statistics were used for data processing: quantitative indicators (haematological and biochemical parameters) are presented as the means ± standard deviations for normally distributed data or the medians with interquartile ranges for nonnormally distributed data. The frequency indicators (frequency of microorganism isolation and presence of resistance genes) are presented as absolute and percentage values.

Pearson’s χ² test was used to compare the frequency of microorganism isolation between the dogs with CPV-2 and the clinically healthy animals, and Fisher’s exact test was used for small sample sizes. A p value of < 0.05 was considered to indicate statistical significance.

To assess the correlations between the presence of resistance genes and phenotypic resistance, a 2 × 2 contingency table was constructed for each gene and the corresponding class of antimicrobial drugs. The sensitivity phenotype was interpreted according to the categories S/I/R (sensitive/intermediate/resistant); in the statistical analysis, only isolates in the R category were considered “resistant”, while the isolates in the S and I categories were combined into the “nonresistant” group. The presence or absence of resistance genes was determined by PCR. For each gene–phenotype pair, the proportion of correspondence (%), odds ratio (OR) with 95% confidence interval, and Fisher’s exact test p values were calculated to assess the statistical significance of the differences. For tables with zero values in the cells, the Haldane–Anskombs correction (adding 0.5) was applied. The criterion for statistical significance was considered to be p < 0.05.

All calculations were performed using Microsoft Excel 2019 and Statistica v.13.

This study was conducted in accordance with the principles of ethical research involving animals, as outlined in the National Institutes of Health Guide for the Care and Use of Laboratory Animals. All animal procedures were approved by the Institutional Animal Care and Use Committee (IACUC). Blood samples were collected from dogs with the informed consent of their owners and in compliance with ethical guidelines for the humane treatment of animals. The data obtained in this study will be used solely for scientific purposes and will be presented with respect for the confidentiality and privacy of both the dogs and their owners.

Between January 2020 and December 2024, veterinary clinics in the city of Kostanay treated 2,831 dogs. Of these dogs, 549 presented with symptoms of gastrointestinal tract diseases at registration. Laboratory diagnostics (PCR and immunochromatographic testing) confirmed parvovirus enteritis in 7% (n = 198) of the total number of registered dogs. According to clinical records, 80% of these puppies had not received any vaccinations, and 20% had received only one dose of the vaccine, after which they subsequently developed clinical signs of parvovirus enteritis. There were no fully vaccinated animals in the study population. Thus, the group was predominantly unvaccinated, which minimized the variability associated with vaccine-induced immunity. Additionally, none of the dogs had received antibiotics prior to admission to the clinic.

The annual incidence rates are presented in Table 2.

The highest number of cases was recorded in 2021 (128 cases). After 2021, there was a steady decreasing trend in incidence. From 2020 to 2024, the total number of cases decreased by 8.7% (visibility index 91.3%).

As part of the epizootiological monitoring, the outcome of the disease in puppies with confirmed CPV-2 was assessed, with an outcome of fatality recorded for 38 of the 198 dogs (19.2%).

Two groups of dogs were established for microbiota analysis: Group 1 (n = 198) consisted of dogs under 1 year of age with PCR-confirmed parvovirus enteritis (CPV-2⁺), and Group 2 (n = 200) consisted of clinically healthy dogs (control group). The main risk factor in Group 1 was a lack of vaccination. The species composition and frequency of bacterial isolation are presented in Table 3.

A greater number of bacterial isolates (n = 72) were obtained from dogs with parvovirus enteritis than from healthy dogs (n = 59), indicating increased bacterial contamination associated with viral infection. The same bacterial species were predominant in both groups: E. coli, S. aureus, and Klebsiella spp.

Comparison of the frequency of isolation between the groups revealed that gram-negative bacteria were isolated slightly more often in dogs infected with CPV-2 (n = 198) than in clinically healthy animals (35.4% vs. 29.5%; χ² = 1.32; p = 0.25; 95%). No statistically significant differences were detected in the analysis of individual genera: E. coli –17.7% vs. 15.0% (χ² = 0.52; p = 0.47; 95% CI: −4.6–9.9 p.p.), S. aureus—14.6% vs. 12.0% (χ² = 0.60; p = 0.44), and Klebsiella spp. –4.0% vs. 2.5% (p = 0.41, Fisher’s exact test). Thus, although higher absolute values of bacterial isolation frequency were observed in the CPV-2⁺ group, the differences were not statistically significant.

Most dogs with confirmed CPV-2 showed a characteristic clinical profile of acute viral enteritis. The frequencies of key symptoms are shown in Table 4.

The most common symptoms were pronounced lethargy, apathy, and mucohaemorrhagic diarrhoea, which were observed in all the animals. Repeated vomiting, signs of dehydration, and hyperthermia were observed in most patients, whereas anorexia, pale mucous membranes, tachycardia, and weak pulse were less common but also clinically significant. Less frequently, intestinal atony, abdominal wall tenderness, and isolated signs of systemic involvement, including prolonged capillary refill and muffled heart sounds, were recorded.

Comparative analysis of the clinical and laboratory data revealed that the severity of parvovirus enteritis varied significantly depending on the type of bacterial coinfection. The detailed differences in clinical signs and laboratory parameters are shown in Table 5.

The most pronounced disorders were observed in dogs with CPV-2 and Klebsiella spp. infection, which was accompanied by a septic course, profound haematological shifts, pronounced hypoproteinaemia, and increased renal and hepatic dysfunction, as indicated by the valuer of these markers. Animals with CPV-2 + E. coli infection had severe gastrointestinal tract damage, significant electrolyte and protein loss, and pronounced leukopaenia. Coinfection with S. aureus presented a more moderate clinical picture but was characterized by a protracted inflammatory process and a longer recovery period. The results of the combined clinical, haematological, and biochemical analysis emphasize that the type of bacterial agent significantly affects the severity of the disease and the prognosis.

The antibiotic resistance of opportunistic microorganisms isolated from dogs with parvoviral enteritis (n = 198) and from clinically healthy animals (n = 200) was investigated. The results revealed a high level of multidrug resistance (MDR), particularly among isolates from diseased animals (Table 5).

The phenotypic resistance rates of E. coli and Klebsiella spp. isolated from dogs with parvovirus enteritis and clinically healthy animals to the main classes of antimicrobial drugs are shown in Table 6.

E. coli isolates obtained from dogs with parvovirus enteritis exhibited the highest rates of resistance to tetracycline (57.1%) and ofloxacin (34.3%), followed by ciprofloxacin (25.7%) and cefpodoxime (25.7%). The rates of resistance to ampicillin and amoxicillin were 20.0%, while a low rate of resistance to aminoglycosides was observed (<6%). None of these isolates were resistant to meropenem (0%).

E. coli isolates from clinically healthy dogs also showed resistance mainly to fluoroquinolones (norfloxacin—43.3%, ofloxacin—23.3%), with lower rates of resistance to tetracyclines (23.3%) and cephalosporins (up to 16.7%).

Klebsiella spp. were highly resistant to β-lactams in both groups, with rates of resistance to ampicillin and amoxicillin of 100% in dogs with parvovirus and 60–80% in healthy dogs. Significant resistance to fluoroquinolones (up to 62.5%) and tetracyclines (60–62.5%) was also detected. Resistance to meropenem was detected only in animals infected with CPV-2 (37.5%).

Analysis of phenotypic resistance revealed that the proportions of resistant isolates of E. coli and Klebsiella spp. did not significantly differ between the group of dogs with CPV-2 and the group of clinically healthy animals (p > 0.05 for all microorganism–antibiotic combinations). The lone exception was tetracycline for E. coli isolates, for which a significantly higher prevalence of resistance was recorded in dogs infected with CPV-2 (57.1% vs. 23.3%; OR = 4.28; 95% CI: 1.46–12.89; p = 0.011).

Data on S. aureus resistance are presented in Table 7.

The table shows the resistance rates of staphylococci isolated from dogs with parvovirus enteritis and clinically healthy animals to antimicrobial drugs.

Staphylococci isolates from the group of dogs with parvovirus enteritis exhibited the highest rates of resistance to tetracycline (48.3%), erythromycin (27.6%), penicillin (24.1%) and tylosin (24.1%). Moderate resistance to ampicillin and trimethoprim/sulfamethoxazole (6.9% each) was detected. A low rate of resistance to aminoglycosides was observed (<6.9%), and no resistance to gentamicin was detected.

In the group of healthy dogs, the highest resistance rates were associated with penicillin (33.3%) and ampicillin (37.5%). The rate of tetracycline resistance (16.7%) was significantly lower than that of isolates from dogs with parvovirus, similar to the resistance profile for macrolides (8.3–12.5%).

Thus, S. aureus isolates from both groups were characterized by β-lactam resistance, but macrolide- and tetracycline-resistant phenotypes were more common in CPV-2⁺ animals.

Statistical analysis revealed that for most antibiotics, the differences between the groups were nonsignificant (p > 0.05). However, the incidence of tetracycline-resistant strains was significantly higher in the dogs with parvovirus enteritis (48.3% (14/29) vs. 16.7% (4/24); OR = 4.67; 95% CI: 1.28–17.08; p = 0.021).

Tables 8, 9 present the distribution of genes associated with the resistance of opportunistic microorganisms to various classes of antibiotics.

As shown in Table 8, analysis of resistance determinants revealed that the greatest number of genes detected were associated with resistance to β-lactams and aminoglycosides. In E. coli isolates from dogs with parvoviral enteritis, the most frequently detected genes were blaTEM (20.0%), OXA (14.3%), tetB (11.4%), and the aminoglycoside resistance genes StrA (11.4%) and StrB (11.4%).

In E. coli isolates from clinically healthy dogs, the predominant genes were blaTEM (16.7%), tetA (13.3%), tetB (6.7%), aadB (6.7%), and qnr (6.7%).

In Klebsiella spp. (n = 13), the most prevalent genes included blaTEM (46.2%), OXA (30.8%), tetB (30.8%), aphA1 (23.1%), qepA (15.4%), and SUL1/SUL3 (15.4% each).

Overall, β-lactamase genes (blaTEM and OXA) were detected in 30 cases (38.5% of all the isolates), aminoglycoside resistance genes (StrA, StrB, aadB, and aphA1) were detected in 28 cases (35.9%), tetracycline resistance genes (tetA and tetB) were detected in 19 cases (24.4%), sulfonamide resistance genes (SUL1 and SUL3) were detected in 10 cases (12.8%), and fluoroquinolone resistance genes (qepA and qnr) were detected in 9 cases (11.5%).

Molecular analysis of S. aureus isolates revealed that genes encoding resistance to β-lactam antibiotics were the most frequently detected. The blaZ gene was detected in 12 isolates (22.6%) and was more frequently detected in dogs with parvoviral enteritis (24.1%) than in clinically healthy dogs (20.8%). The mecA gene, associated with methicillin resistance (MRSA), was not detected in any of the samples (Table 9).

Among the macrolide resistance genes, ermC (7.5%) and ermB (7.5%) were detected, and their distributions were similar between the groups. Aminoglycoside resistance was mediated by the genes aac(6′)-aph(2″) (5.7%) and aph(3′) (7.5%).

Tetracycline resistance genes were detected in a considerable number of isolates: tetK in 7 isolates (13.2%) and tetM in 4 isolates (7.5%). The prevalence of these genes was greater in dogs with parvoviral enteritis (tetK: 17.2%; tetM: 10.3%) than in clinically healthy dogs (tetK: 8.3%; tetM: 4.2%).

No sulfonamide resistance genes (dfrG or dfrK) were detected in the S. aureus isolates examined.

The correlations between the presence of resistance genes and phenotypic resistance in bacterial isolates from dogs was analysed (Table 10).

High concordance between the genotype and phenotype was revealed for β-lactams: blaTEM and blaZ showed a compliance of 88.9–100% (OR 9.78–98.53; p < 0.001). Significant overlap was also noted for the aminoglycoside-associated determinants aac(6)-aph2 and aadB (100% compliance; p < 0.01), as well as for the genes sul1, sul3, tetA, tetB and tetK, which confer resistance to sulfonamides and tetracyclines (90–100% compliance; p < 0.01). The qnrA and ermC genes were also significantly associated with resistance to fluoroquinolones and macrolides, respectively. Thus, most of the studied determinants have high diagnostic significance for predicting phenotypic resistance in bacterial isolates from dogs.

Chromogenic media were used to isolate and identify E. coli STEC and O157, enabling clear differentiation between Shiga toxin-producing E. coli (STEC) and serotype O157: H7 verotoxin-producing E. coli.

Among the 65 E. coli isolates, Shiga toxin-producing strains (STECs) were identified in six cases (9.2%)—four strains from dogs with parvoviral enteritis and two from clinically healthy animals. In addition, E. coli O157: H7—a strain of high epidemiological significance—was detected in one dog with confirmed CPV-2 infection.

The enterotoxigenic properties of the S. aureus isolates were evaluated using an enzyme-linked immunosorbent assay (ELISA). Differences were observed in the ability to produce enterotoxins A, B, C, D, and E. Among the 53 S. aureus isolates, the ability to produce enterotoxins (SEA-SEE) was detected in two strains (3.8%), both of which were isolated from dogs with parvoviral enteritis, with one producing enterotoxin D and the other, enterotoxin E. The remaining isolates (n = 51; 96.2%) were nonenterotoxigenic.