Molecular characterization of bovine viral diarrhea virus and host genetic immune and biochemical responses in diarrheic buffalo calves

TL;DR

This study investigates the genetic and biochemical responses in diarrheic buffalo calves infected with bovine viral diarrhea virus (BVDV) to identify potential biomarkers for disease prediction and prevention.

Contribution

The study introduces a novel approach using gene expression profiles and nucleotide sequence variations to predict and prevent diarrhea in buffalo calves through marker-assisted selection.

Findings

BVDV was detected in 20% of diarrheic buffalo calves with high viral loads.

Gene expression levels of immune and antioxidant markers were significantly altered in diarrheic calves.

Serum levels of acute phase proteins and biochemical markers were significantly different between diarrheic and healthy calves.

Abstract

Buffalo calves are highly susceptible to neonatal calf diarrhea (NCD), a major cause of morbidity, mortality, and economic loss in livestock production. Among the viral agents responsible, bovine viral diarrhea virus (BVDV) is one of the most common causes of NCD. The infection leads to significant financial losses due to calf mortality, treatment costs, reduced growth performance, and increased susceptibility to secondary infections. The study’s goals were to examine the connections among SNPs, gene expression, the serum profile of biochemical and APPs marker changes, and the molecular detection and prevalence of BVDV in Egyptian diarrheal calves. Blood samples were obtained from 100 neonatal buffalo calves that were diarrheal and 100 that seemed healthy. The blood samples were then separated into EDTA tubes for whole blood collection used for RNA extraction and plain tubes (without anticoagulant) for serum collection. One hundred fecal samples were collected from diarrheic group for BVD screening using polymerase chain reaction (PCR), and those that tested positive with relatively high viral loads were further examined using PCR to amplify specific gene regions: the 5′UTR gene for BVD. Gene expression profile and nucleotide sequence variation for immune and antioxidant markers were assessed in healthy and diarrhea affected calves. BVDV was detected in 20% of the samples, according to PCR data. When the detected strains were matched to reference strains in Genbank, their identities ranged from 84.1 to 100%. Five identified samples’ partial 5′UTR gene nucleotide sequences were uploaded to GenBank and assigned the accession codes PV243153, PV243154, PV243155, PV243156, and PV243157. Diarrheic group gene expression levels of SLC11A1, CD14, PTX3, IRF3, and ST1P1 were considerably (P < 0.05) higher than those of the control group. PRDX2, PRDX6, and GPX, on the other hand, were in the opposite range. Differences in the nucleotide sequences of the genes under investigation were observed between the diarrheic and healthy calves. Serum levels of APPs (Hp, SAA, Cp), ALT, AST, GGT, LDH, BUN, creatinine, triglyceride, cortisol and CRP were significantly (P˂0.05) increased in diarrheal buffalo calves, while serum levels of glucose, total protein, albumin, globulin, calcium, phosphorus, sodium, copper, zinc and iron were decreased. The findings of the study suggest that BVD is widespread in Egypt. The study’s conclusions suggest that by using gene expression profiles and nucleotide sequences in genes related to immunity and antioxidants, buffalo calves could be chosen by marker-assisted selection (MAS) to predict and prevent diarrhea. Biochemical and APPs markers, as well as gene expression profiles and nucleotide sequence of genes under investigation, may also be used as proxy biomarkers for buffalo calves’ diarrhea in order to make an effective management protocol, create effective vaccines, control strategies, and identify the most vulnerable risk period for disease occurrence.

The online version contains supplementary material available at 10.1038/s41598-026-40635-y.

Figures

Agarose gel electrophoresis showing PCR amplification of the target gene fragment. Lanes 1 10: DNA samples from buffalo calves; Lane N: negative control (no template DNA); Lane P: positive control; Lane L: 100 bp DNA ladder (100–1000 bp). Specific PCR amplicons of the expected size (200 bp) were observed in lanes (1–3, 9, 10), confirming the presence of the target gene.

Phylogenetic tree based on the partial 5′ untranslated region (5′UTR) nucleotide sequences of bovine viral diarrhea virus (BVDV) isolates from diarrheic buffalo calves and reference BVDV-1 strains retrieved from GenBank. The tree was constructed using the neighbor-joining method with 1,000 bootstrap replications in MEGA software. Bootstrap values above 80% are shown at the branch nodes. The blue circles indicate the BVDV isolates identified in the present study. The reference strains representing different subgenotypes are labeled with their GenBank accession numbers and isolate names. The stu

Percent nucleotide identity and divergence matrix among BVDV strains based on partial 5′-UTR sequences. The matrix illustrates pairwise percent identity (upper right triangle) and genetic divergence (lower left triangle) between 28 bovine viral diarrhea virus (BVDV) strains. Strain identifiers and accession numbers are listed on the right. Higher percent identity values (darker shading) indicate closer genetic relationships among isolates. Egyptian BVDV field strains (highlighted) show high sequence similarity with BVDV-1a reference strains, suggesting their close genetic relatedness within th

Normal and diarrhea-affected caves have different immune and antioxidant genes transcript levels. When *p* is less than 0.05, significance is indicated by the symbol *.

Full text

Introduction

Even though they are typically raised in harsh conditions and have limited reproductive and productive ability, buffaloes are the primary source of high quality meat and milk in Egypt and some other developing nations^1^. Newborn calves are an important component of livestock production worldwide, whether for breeding or meat production^2^.

Neonatal calf diarrhea (NCD), the world’s largest cause of calf diseases and mortality, costs dairy farmers a lot of money due to treatment costs, labor costs, poor performance, growth retardation, and fatalities^3^. Despite advances in chemotherapeutic therapies and scientific research, the morbidity and fatality rate for neonatal calf diarrhea remain high^3,4^. NCD is a complex illness that can occur alone or in conjunction with different etiologic agents, such as bacteria, viruses, and protozoa, and is caused by the interaction of environmental factors, such as management, nutrition, and physiological factors, and calves themselves^5^. The majority of studies looking into the causes of calf diarrhea have focused on sick calves, according to Sedky et al.^6,7^. However, certain pathogens, especially viruses, may be consistently present in healthy calves^8^. Bovine viral diarrhea virus (BVDV) is not a major contributor to neonatal calf diarrhea (NCD) in all regions, particularly in countries where effective eradication programs have been implemented and may not act as the primary cause of diarrhea but rather as a facilitator, compromising the immune system and increasing susceptibility to secondary enteric infections that manifest at a later stage according to Azkur et al.^9^. In Egypt, it has been discovered in both diarrheal and asymptomatic calves, suggesting that it is widely distributed and may have a role in subclinical illnesses^10^. They are important as herd-level indicators for biosecurity and disease control since they affect the herd’s overall health as well as reproductive performance^11^.

In the global cow business, bovine viral diarrhea (BVD) is a highly contagious disease that results in large financial losses. Bovine viral diarrhea virus (BVDV), the cause of BVD, is a member of the Pestivirus genus of the Flaviviridae family, which also contains border disease virus (BDV) and classical swine fever virus (CSFV)^12^. Although BVDV naturally infects cattle of all breeds and ages, it can also infect goats, sheep, camels, pigs, and giraffes. Animals with the infection show signs of reproductive problems, blood or mucous feces, severe mucosal ulceration, and high body temperature^13^. The two biotypes of BVDV are cytopathogenic (cp.) and non-cytopathogenic (ncp), depending on whether the virus causes a cytopathogenic effect (CPE) in infected cells^14^. According to Oguejiofor et al.^15^, The cytopathic (CP), non-cytopathic (nCP) biotypes of BVDV are distinguished by their behavior in infected cell cultures, where CP strains induce visible cytopathic effects, whereas nCP strains do not. Biologically, nCP BVDV is primarily responsible for establishing persistent infections (PI) in fetuses following transplacental infection, while CP strains are more often associated with reproductive failures and abortions. When a persistently infected animal is subsequently exposed to a homologous CP BVDV strain, mucosal disease may develop, which is typically fatal^16^.

A single-stranded, positive-sense RNA virus, BVDV has a genomic size of about 12.3 kb. There is only one open reading frame (ORF) in its genome, which is surrounded by 3’-UTR and 5′-untranslated region (5’-UTR). Although the 5’-UTR is frequently utilized to classify BVDV genotype and subtypes^17^, this approach may result in viral classification that is imprecise or lacks sufficient statistical evidence. Novel primer sets have been created by researchers to subtype BVDV by targeting the NS3-NS4A of BVDV-1 (526 bp amplicon) and NS5B of BVDV-2 (728 bp amplicon). All 118 BVDV-1 and 88 BVDV-2 complete/near-complete genomes (CNCGs) from GenBank have subtypings that are accurately reproduced by this categorization^18^. According to Palacios et al.^19,20^, BVDV is divided into three genotypes: BVDV-1 (Pestvirus A), BVDV-2 (Pestvirus B), and BVDV-3 (Pestvirus H or HoBi-like virus). Of these, BVDV-1 presently has at least 22 subtypes (1a-1v), while BVDV-2 has at least 4 subtypes (2a-2d). Eight non-structural proteins (Npro, p7, NS2, NS3, NS4A, NS4B, NS5A, NS5B) and four structural proteins (C, Erns, E1, E2) are produced by post-translational cleavage of the single ORF-encoded big polyprotein in ncp BVDV isolates^21^. Recombination of non-homologous RNAs is the main cause of the significant genetic variability seen in BVDV isolates, as well as other RNA viruses. In addition to increasing genetic diversity, homologous RNA recombination hinders BVDV diagnosis and reduces the effectiveness of the BVDV vaccination^22^. The cattle business has been severely impacted by BVD, a serious viral illness that threatens animal health^23^. Numerous diagnostic techniques, such as etiological, serological, and molecular methods for BVDV detection, have been developed in order to quickly and accurately diagnose BVDV infection.

Blood biochemical analyses are a useful technique for evaluating general health because they offer a wealth of information on an animal’s nutritional state, general health, and general well-being^24^. Specific blood parameter deviations from accepted normal ranges can help with disease differential diagnosis by providing information on the extent of tissue damage and the severity of infection^25^.

Hepatocytes release a collection of proteins called acute phase proteins (APPs) into the bloodstream. These proteins are essential for reducing pathological damage, reestablishing homeostasis, and limiting microbial development in infected animals without the need for antibodies^26^. Pregnancy, lactation, age, sex, food, and environmental factors are among the physiological and pathological factors that influence blood levels of APPs^25^. If the blood concentrations of these proteins increase or decrease in response to infection, inflammation, or other internal and external stimuli, they can be classified as either positive or negative APPs. Since response patterns vary significantly between species, these changes provide valuable diagnostic and prognostic insights^27,28^. According to Afify et al.^10^, serum amyloid A (SAA) is another positive APP that usually rises during the acute phase response, and haptoglobin (Hp) is the main acute phase protein in ruminants.

Innovative molecular genetic techniques could enhance animal health and support disease prevention^29^. Numerous genetic markers, primarily single nucleotide polymorphisms (SNPs), can be used to correctly predict livestock disease susceptibility and resistance^30^. This implies that host genotypes differ in their level of disease resistance or vulnerability^31^.

In Egyptian diarrheal calves, research on APPs, biochemical changes, SNPs, gene expression, molecular detection, and BVDV prevalence is still in its early stages. The genetic links between local strains and previously identified strains, both domestically and internationally, are also being elucidated using phylogenetic analysis. Therefore, the purpose of this study was to examine the relationship between calf diarrhea and SNPs, gene expression, the serum profile of APPs and biochemical marker alterations, and other risk factors. Along with investigating the molecular detection and prevalence of BVDV in Egyptian diarrheal calves, this study also plans to do phylogenetic analysis to elucidate the genetic relationships between local strains and those that have already been described locally and internationally.

Results

Clinical findings

Various degrees of diarrhea, anorexia, emaciation, weakness, dullness, depression, pale mucous membrane, trouble standing, sunken eye, varied degrees of dehydration, straining with arched back, and elevated tail were among the clinical signs observed in the diarrheal calves. The presence of diarrhea was determined at the time of sampling based on fecal consistency and color. Diarrhea was defined as liquid or semi-liquid feces (fecal score ≥ 3 on a 1–4 scale), often accompanied by dehydration or soiling of the perineum. Normal feces (score 1–2) were considered non-diarrheic. The color of the fecal discharge varied from pale yellow to yellowish to greenish, and some fecal samples contained mucus and clotted blood. Furthermore, diarrheic group (DG) differs from control group (CG) in terms of rectal body temperature, pulse rate, and respiration rate (39.61 ± 0.1 °C, 99 ± 0.1 beats/min, and 48.4 ± 0.2 breaths/min as opposed to 38.61 ± 0.1 °C, 89 ± 0.1 beats/min, and 38.4 ± 0.4 breaths/min, respectively).

PCR detection of viral pathogens

Only BVDV RNA was detected by the assays performed. Other common viral, bacterial and protozoal agents were not identified because either they were not targeted by molecular assays in this screening, or detection may have been limited by sample type, assay sensitivity, or intermittent shedding. The bovine viral diarrhea virus (BVDV) was detected in 20% of the 100 fecal samples from buffalo calves that had diarrhea after they were exposed to PCR analysis. A clear band at 200 bp was produced by PCR directed at the 5’ UTR region (Fig. 1).

Fig. 1. Agarose gel electrophoresis showing PCR amplification of the target gene fragment. Lanes 1 10: DNA samples from buffalo calves; Lane N: negative control (no template DNA); Lane P: positive control; Lane L: 100 bp DNA ladder (100–1000 bp). Specific PCR amplicons of the expected size (200 bp) were observed in lanes (1–3, 9, 10), confirming the presence of the target gene.

Homology and genetic evolution analysis of BVD 5’UTR gene

The 5′UTR regions of BVDV-positive samples were successfully amplified using the primers listed in Table 1, producing a single target fragment of approximately 200 bp. Electrophoresis results confirmed the presence of this fragment, as shown in Fig. 1, consistent with the expected amplicon size. The purified PCR products were sequenced, and sequence alignment and homology analyses were performed using MegAlign software. The obtained 5′UTR sequences showed nucleotide identity ranging from 84.1 to 100% when compared with representative BVDV reference strains (Figs. 2 and 3). Reference sequences representing various subgenotypes are identified by their GenBank accession numbers and isolate names. Phylogenetic analysis revealed that the studied isolates clustered within the BVDV-1a and BVDV-1b subgenotypes. The newly characterized 5′UTR gene sequences from buffalo calves in South Sinai, Egypt, were deposited in GenBank under the accession numbers PV243153, PV243154, PV243155, PV243156, and PV243157.

Fig. 2. Phylogenetic tree based on the partial 5′ untranslated region (5′UTR) nucleotide sequences of bovine viral diarrhea virus (BVDV) isolates from diarrheic buffalo calves and reference BVDV-1 strains retrieved from GenBank. The tree was constructed using the neighbor-joining method with 1,000 bootstrap replications in MEGA software. Bootstrap values above 80% are shown at the branch nodes. The blue circles indicate the BVDV isolates identified in the present study. The reference strains representing different subgenotypes are labeled with their GenBank accession numbers and isolate names. The studied isolates clustered within the BVDV-1a and BVDV-1b subgenotypes. The scale bar represents 0.01 nucleotide substitutions per site.

Fig. 3. Percent nucleotide identity and divergence matrix among BVDV strains based on partial 5′-UTR sequences. The matrix illustrates pairwise percent identity (upper right triangle) and genetic divergence (lower left triangle) between 28 bovine viral diarrhea virus (BVDV) strains. Strain identifiers and accession numbers are listed on the right. Higher percent identity values (darker shading) indicate closer genetic relationships among isolates. Egyptian BVDV field strains (highlighted) show high sequence similarity with BVDV-1a reference strains, suggesting their close genetic relatedness within the BVDV-1a genotype.

Table 1. Primer sequences, target genes, and amplicon sizes for Bovine Viral Diarrhea Virus (BVDV) detection.Target agentTarget genePrimer sequence(5’-3’)Length of amplified product (bp)Reference BVD

5’UTR GGGNAGTCGTCARTGGTTCG200 bp ^120^ GTGCCATGTACAGCAGAGWTTTTBVD: Bovine viral diarrhea.^120^ Zulauf, B.J. (2007): Multiplex Real-Time PCR in the Detection and Differentiation of Bovine Respiratory Disease Pathogens Master of Science thesis of presented on June 14th, 2007. Oregon State University.

Patterns for transcript levels of immune indicators

The transcript patterns for the evaluated immunological and antioxidant markers were shown in Fig. 4. When compared to healthy calves, calves with diarrhea had noticeably higher levels of mRNA expression level for the genes SLC11A1, CD14, PTX3, IRF3, and ST1P1. GPX, PRDX2, and PRDX6 levels, however, dropped. The lowest mRNA expression level of each gene was 0.43 ± 0.12 for PRDX6, whereas the highest level of mRNA expression for diarrheic calves was 2.37 ± 0.12 for SLC11A1. GPX had the highest mRNA expression level (1.66 ± 0.17), while PTX3 had the lowest (0.45 ± 0.13), of all the genes analyzed in the healthy calves.

Fig. 4. Normal and diarrhea-affected caves have different immune and antioxidant genes transcript levels. When p is less than 0.05, significance is indicated by the symbol *.

The genes SLC11A1, CD14, PTX3, IRF3 and ST1P1 had significantly greater gene expression levels in diarrhea -affected calves compared to healthy ones. However; PRDX2, PRDX6, and GPX levels decreased. The highest mRNA expression level of mRNA for diarrheic calves was 2.37 ± 0.12 for SLC11A1, whereas the lowest amount of each gene was 0.43 ± 0.12 for PRDX6. Out of all the genes examined in the healthy calves, GPX had the highest possible level of mRNA (1.66 ± 0.17), whereas PTX3 had the lowest amount (0.45 ± 0.13).

Genetic polymorphisms of immune and antioxidant genes

Using PCR-DNA sequence verdicts, the SLC11A1 (429-bp), CD14 (360-bp), PTX3 (388-bp), IRF3 (430-bp), PRDX2 (425-bp), PRDX6 (437-bp), GPX (267-bp), and ST1P1 (455-bp) genes were found to have different SNPs in the amplified DNA bases linked to diarrhea. Based on the DNA sequence variations between immunological and antioxidant indicators examined in the calves under study and the reference gene sequences retrieved from GenBank Figures (S1–S8), all of the identified SNPs were approved. The coding DNA sequences of the affected calves differed from those of the healthy calves due to the exonic region abnormalities that were seen in Table 2 in all of the immunological and antioxidant markers tested. Using DNA sequencing of immune and antioxidant genes, 13 SNPs were found; seven of them were non-synonymous and six were synonymous.

Table 2. Diarrheic and healthy calves’ immunological and antioxidant marker distributions with a single base differential and possible genetic change.GeneSNPsHealthyn = 100Diarrhean = 100Totaln = 200kind of inherited changeChi squareX2P valueAmino acid order and sort SLC11A1 A292G73/100-/10073/200Non-synonymous114.90.00198 T to A CD14 T223A39/100-/10039/100Non-synonymous48.40.00175 S to T PTX3 C65G-/10047/10047/200Non-synonymous62.60.00122 A to GT145C-/10061/10061/200Synonymous88.40.00149 LC353T58/100-/10058/200Non-synonymous81.60.001118 A to V IRF3 G81C53/100-/10053/200Synonymous72.10.00127 TC270T86/100-/10086/100Synonymous150.80.00190 D PRDX2 G151T-/10079/10079/100Non-synonymous133.20.00151 A to S PRDX6 T255C31/100-/10031/100Synonymous36.60.00185 NG419T48/100-/10048/100Non-synonymous63.10.001140 K to N GPX C64T65/100-/10065/100Non-synonymous96.20.00122 P to S ST1P1 T138C49/100-/10049/200Synonymous64.90.00146 DC405T72/100-/10072/200Synonymous112.50.001135 DSLC11A1: Solute Carrier Family 11 Member 1; CD14: Cluster of Differentiation 14; PTX3: Pentraxin 3; IRF3: Interferon Regulatory Factor 3; PRDX2: Peroxiredoxin 2; PRDX6: Peroxiredoxin 6; GPX : Glutathione Peroxidase; ST1P1: stress-induced phosphoprotein 1; GAPDH: Glyceraldehyde-3-Phosphate Dehydrogenase. A= Alanine; D= Aspartic acid; G= Glycine; H= Histidine; K= Lysine; L = Leucine; N= Asparagine; P= Proline; S = Serine; T= Threonine; and V = Valine.

A significant difference was detected in the frequencies of all examined genes SNPs among diarrheic and healthy calves (p < 0.005). Chi-square analysis was carried out for comparison of the distribution of all identified SNPs in all genes between diarrheic and healthy calves. Total chi-square value showed significant variation among the identified SNPs in all genes between resistant and affected animals (p < 0.05) (Table 2).

The discriminant analysis for the order of gene types and health status was displayed in Table 3. The organization’s outcomes demonstrated that the model correctly identified both healthy and diarrheal calves in 100% of the cases. These findings suggest that the SNP markers in the model have a high degree of discriminatory power and could be helpful as prospective genetic markers for calves’ susceptibility to diarrhea.

Table 3. Discriminant analysis for classification of type of genes and healthy status of examined calves.Predicted group membershipTotalHealthyDiseasesCountHealthy1000100Diseased0100100%Healthy100.00.0100.0Diseased0.0100.0100.0

Biochemical and APPs profile

Table 4 demonstrated that diarrhea in buffalo calves was linked to a profound innate immune response, as evidenced by a significant (P˂0.05) rise in the amounts of APPs (Hp, SAA, Cp), ALT, AST, GGT, LDH, BUN, creatinine, triglyceride, cortisol and CRP in DG relative to CG. In contrast, DG’s levels of glucose, total protein, albumin, globulin, calcium, phosphorus, sodium, copper, zinc and iron, considerably (P˂0.05) dropped compared to CG.

Table 4. Biochemical and APPs profile of calves suffering from diarrhea compared to the control healthy group.ParametersHealthy calvesDiarrheic calvesGlucose (mg/dl)110 ± 5.760.6 ± 2.9Cholesterol (mg/dl)80 ± 0.581 ± 0.5Triglyceride (mg/dl)40.3 ± 0.850.3 ± 0.8Total protein (g/dl)5.6 ± 0.055 ± 0.05Albumen (g/dl)3.8 ± 0.053 ± 0.05Globulin (g/dl)1.4 ± 0.051.5 ± 0.05Urea (mg/dl)32 ± 0.541 ± 0.5Createnine (mg/dl)0.7 ± 0.081.2 ± 0.05AST (U/L)46 ± 0.556 ± 0.5ALT (U/L)34 ± 0.543.3 ± 1.2GGT (U/L)6.4 ± 0.515 ± 1.5LDH (U/L)55.3 ± 1.487.6 ± 1.4CPK (U/L)2.8 ± 0.089.6 ± 0.4CRP (mg/dl)60.6 ± 2.9110 ± 5.7cTnI (ng/ml)60.6 ± 2.9110 ± 5.7Cortisol (U/L)4.8 ± 0.110.4 ± 0.3Calcium (mg/dl)7 ± 0.056.5 ± 0.05Phosphorus (mg/dl)6.5 ± 0.085.4 ± 0.2Sodium (mmol/l)156.3 ± 1.8141 ± 0.5Potassium (mmol/l)5.4 ± 0.055.8 ± 0.05(Chloride (mmol/l90 ± 0.576 ± 0.5Copper (mg/dl)118 ± 1.585 ± 2.8Zinc (mg/dl)164.3 ± 2.3113 ± 3Iron (mg/dl)6.9 ± 0.056.3 ± 0.1Hp (ng/ml)40 ± 0.561 ± 0.5SAA (mg/l)3.9 ± 0.39.7 ± 0.4Cp (mg/dl)26 ± 0.545.3 ± 2*AST: Aspartate transaminase; ALT: Alanine aminotransferase; GGT: gamma-glutamyl transferase; LDH: Lactic Dehydrogenase; CPK: Creatine phosphokinase; CRP: C-reactive protein; cTnI: Cardiac troponin I; Hp: Haptoglobin; SAA: Serum amyloid A; Cp: Ceruloplasmin. The symbol * denotes significance when P˂0.05.

Correlation between gene expression pattern of immune and antioxidant genes and serum profile of biochemical and APPs biomarkers in diarrheic buffalo calves

A strong positive correlation was observed between the expression of immune- and stress-related genes and several serum biochemical parameters in diarrheic buffalo calves (Table 5). SLC11A1 showed significant associations with Cp, cTnI, TP, albumin, CPK, cortisol, P, Fe, Cu, LDH, and creatinine, highlighting its role in metabolic and inflammatory regulation. CD14 correlated positively with Hp, TG, AST, and Na, but negatively with Ca, indicating its involvement in acute-phase and electrolyte responses. PTX3, IRF3, and PRDX2 were strongly linked to hepatic, metabolic, and oxidative stress markers (TP, albumin, glucose, urea, CHO, GGT, LDH, CRP, Cu, Fe, cortisol). Their association with antioxidant elements (Cu, Fe) and energy metabolites (glucose, CHO) supports their role in oxidative and cellular stress, while PRDX2’s link with CPK and K suggests muscular involvement. NDUFS6 correlated with Cl, reflecting mitochondrial adjustment to ionic imbalance, and GPX with ALT and Zn, confirming its hepatoprotective antioxidant function. ST1P1 showed perfect correlations with multiple inflammatory and metabolic indicators, underscoring its key role in systemic stress responses.

Table 5. Correlation between gene expression pattern of immune and antioxidant genes and serum profile of biochemical and acute phase proteins biomarkers in diarrheic buffalo calves.GeneBiochemical profileSLC11A1Cp (r = 1, P = 0.01), cTnI (r = 1, P = 0.003), TP (r = 1, P = 0.001), albumin (r = 1, P = 0.001), CPK (r = 1, P = 0.001), cortisol (r = 1, P = 0.001), P (r = 1, P = 0.001), Fe (r = 1, P = 0.001), Cu (r = 1, P = 0.009), LDH (r = 1, P = 0.013), creatinine (r = 1, P = 0.019).CD14Hp (r = 0.998, P = 0.03), TG (r = 0.998, P = 0.04), AST (r = 0.998, P = 0.03), Ca (r=-1, P = 0.01), Na (r = 0.998, P = 0.03).PTX3cTnI (r = 0.999, P = 0.03), Glucose (r = 1, P = 0.03), CHO (r = 0.999, P = 0.02), TP (r = 0.999, P = 0.03), albumin (r = 0.999, P = 0.03), urea (r = 0.999, P = 0.02), GGT (r = 1, P = 0.001), CRP (r = 1, P = 0.01), LDH (r = 0.999, P = 0.02), creatinine (r = 1, P = 0.019), cortisol (r = 0.999, P = 0.03), K (r = 1, P = 0.01), Cu (r = 0.999, P = 0.02), Fe (r = 1, P = 0.03).IRF3Hp (r = 0.997, P = 0.04), cTnI (r = 0.999, P = 0.03), glucose (r = 1, P = 0.01), CHO (r = 0.999, P = 0.02), TP (r = 0.998, P = 0.03), albumin (r = 0.998, P = 0.03), urea (r = 0.999, P = 0.02), GGT (r = 1, P = 0.003), LDH (r = 0.999, P = 0.02), CRP (r = 0.998, P = 0.03), cortisol (r = 0.998, P = 0.03), P (r = 1, P = 0.01), Cu (r = 0.999, P = 0.02), Fe (r = 0.999, P = 0.03).PRDX2Hp (r = 0.999, P = 0.03), cTnI (r = 0.997, P = 0.04), glucose (r = 1, P = 0.02), CHO (r = 0.998, P = 0.02), TP (r = 0.999, P = 0.02), albumin (r = 0.997, P = 0.02), urea (r = 0.998, P = 0.02), GGT (r = 1, P = 0.003), LDH (r = 0.998, P = 0.03), CPK (r = 0.999, P = 0.02), CRP (r = 0.999, P = 0.02), cortisol (r = 0.999, P = 0.03), K (r = 1, P = 0.01), Cu (r = 0.999, P = 0.02), Fe (r = 0.999, P = 0.03).NDUFS6Cl (r = 0.994, P = 0.04).GPXALT (r = 0.999, P = 0.02), Zn (r = 1, P = 0.001),ST1P1Cp (r = 1, P = 0.03), cTnI (r = 1, P = 0.003), TP (r = 1, P = 0.001), albumin (r = 1, P = 0.001), globulin (r = 1, P = 0.01), creatinine (r = 1, P = 0.001), GGT (r = 0.999, P = 0.03), LDH (r = 1, P = 0.03), CPK (r = 1, P = 0.001), CRP (r = 1, P = 0.01). CRP (r = 1, P = 0.03), P (r = 1, P = 0.009), K (r = 0.999, P = 0.02), Fe (r = 1, P = 0.001).SLC11A1: Solute Carrier Family 11 Member 1; CD14: Cluster of Differentiation 14; PTX3: Pentraxin 3; IRF3: Interferon Regulatory Factor 3; PRDX2: Peroxiredoxin 2; PRDX6: Peroxiredoxin 6; GPX : Glutathione Peroxidase; ST1P1: stress-induced phosphoprotein 1; CHO: Cholesterol; TP: Total protein; AST: Aspartate transaminase; ALT: Alanine aminotransferase; GGT: gamma-glutamyl transferase; LDH: Lactic Dehydrogenase; CPK: Creatine phosphokinase; CRP: C-reactive protein; cTnI: Cardiac troponin I; Hp: Haptoglobin; SAA: Serum amyloid A; Cp: Ceruloplasmin; Ca: Calcium; P: Phosphorus; K: Potassium; Na: Sodium; Cu: Copper; Zn: Zinc; Fe: Iron.

Discussion

Despite the advances in herd management, animal care, stables, animal feeding, cattle industry and timely use of biopharmaceuticals, neonatal calf diarrhea remains a major cause of economic loss in the cattle industry worldwide^32^. Among the most significant etiological agents of diarrhea in newborns of numerous animal species worldwide is BVDV^33^. In addition to being crucial for monitoring the epidemiological state of a protected area, obtaining and characterizing BVDV isolates from the field is also essential for verifying the field protection provided by vaccines and immunizations. The viral strain lacks a particular genetic or structural characteristic (a “notch” or marker) that would enable researchers to readily change or differentiate it when developing vaccine strains. In order to control disease and avoid financial losses, it is critical to identify the disease factor in newborn calves in herds.

There is an important distinction between infectious and nutritional causes of diarrhea in buffalo calves. Although BVDV was detected, its presence does not exclude concurrent nutritional factors. In this study, cases were classified using clinical, management, and laboratory criteria to distinguish between infectious and nutritional diarrhea. This approach minimizes misclassification and clarifies BVDV’s role: detection in febrile, systemically affected calves supports an infectious origin, whereas its presence in calves with recent dietary changes but no systemic signs may indicate an incidental or contributing factor. Future work should apply multiplex diagnostics and standardized feeding assessments to better elucidate mixed etiologies.

In the present investigation, the diarrheal calves had variable degree of diarrhea, dehydration, pale mucous membranes, weakness, emaciation, dullness, depression, and off-food. Additionally, their body temperature, pulse rate, and respiration rate significantly increased in comparison to the healthy calves. The clinical results we obtained were comparable to those reported by^34–40^. Dehydration and metabolic acidosis contribute to increased rectal temperatures due to reduced heat elimination efficiency, followed by a decrease in body temperature. Metabolic acidosis stimulates the sympathetic nervous system, leading to elevated heart rates (tachycardia) and respiratory rates (hyperpnea)^41,42^. According to Radostits et al.^43^, muscle weakness brought on by intracellular potassium escaping, hyperkalemia, and hypoglycemia may be the cause of the observed anorexia, depression, and dullness. However, the production of pyrogenic substances such prostaglandins, hypothalamic thermoregulatory center motivation, infection and inflammation may be responsible for the symptoms of pain and hyperthermia^44^.

Many techniques, such as electron microscopy, antigen-capture ELISA, lateral flow assays, and molecular approaches, can be used to identify the virus because acute infection causes it to be excreted in enormous amounts in the feces (up to 10¹¹ particles/g). Because PCR is such a sensitive molecular technique, it was used to analyze all of the samples gathered for this investigation. Although diarrhea in buffalo calves typically results from mixed infections involving viral, bacterial, and protozoal agents, only BVDV was detected in the present study. This may be attributed to the specific molecular focus on BVDV, while other enteropathogens such as BRV, BCV, ETEC, and protozoa were not included in the screening. In addition, species-specific differences in susceptibility, sampling timing, and regional epidemiological factors could have influenced detection outcomes. The findings suggest that BVDV may play a significant role in enteric disorders of buffalo calves under certain field conditions. However, future investigations using multiplex or metagenomic approaches are recommended to reveal the full spectrum of enteric pathogens and their interactions. The molecular results of our investigation showed that 20% of the calves analyzed in South Sinai Governorate, Egypt, had BVD, which is about the same as the results of the earlier study (21.43% in DAMIETTA, Egypt) by^45^. As reported by Mahranet al.^46–51^, Gabr et al.^48^, Soltan et al.^49^, Mokhtar et al.^50^, Ahmed et al.^51^, the prevalence of BVD infection in the animals under examination in Fayoum, Alexandria, Qaluobia, Ismailia, and Assiut in Egypt, was 6.7%, 8.4%, 10.4%, 3.4%, and 15%, respectively. According to Chang et al.^52,53^, the molecular positive rates for BVDV in Holstein were 7.2 and 1.42%, respectively. Our rates were lower than that of^54^ (22.64%) in Switzerland, and^55^ in Chinese dairy cattle, all of whom had rates of 27.1%. Differences in sample collecting times, sample sizes, sanitary conditions, environmental conditions, and the use of various diagnostic techniques could all be responsible for the discrepancies.

The nucleotide identity of the 5’UTR gene varied from 84.1% to 100%, according to a sequence comparison for BVD strains. The Polish dairy cattle BVDV-1 strain (MK381368) had the lowest homology (83.1%) when compared to representative BVD strains in GenBank, while the BVDV-1 strains isolated from dairy cattle and buffalo in Ismailia, Egypt (KP127973) had the highest homology (100%). Additional strains exhibiting 100% homology include those from Chinese naturally fermented dairy products (KP029825) and American calf (MW713362).

We investigated the alterations in the immunological and antioxidant states of calves with diarrhea in comparison to healthy calves by assessing the mRNA levels of immune and antioxidant genes. The expression of the genes SLC11A1, CD14, PTX3, IRF3 and ST1P1 was much higher in the affected calves than in the healthy ones. However, PRDX2, PRDX6, and GPX levels were decreased.

This study used a PCR-DNA sequencing technique to characterize the immunological (SLC11A1, CD14, PTX3, and IRF3) and antioxidant (PRDX2, PRDX6, GPX, ST1P1) genes in calves with diarrhea and healthy calves. The results demonstrate that there are differences in the SNPs involving the two categories. It is crucial to stress that, in contrast to the similar datasets obtained from GenBank, the polymorphisms discovered and made available in this context offer extra information for the evaluated indicators. No research has looked at the relationship between buffalo calves’ risk of diarrhea and SNPs alongside expression changes in the immune and antioxidant genes. This link is initially shown by the Bubalus bubalis gene sequences used in our study, which were published in PubMed.

Three of the thirteen SNPs found by sequencing were directly linked to calf diarrhea among the genes under investigation. Two of these were non-synonymous changes that were expected to alter the structure and function of proteins. Non-synonymous mutations frequently change the structure or function of proteins, which may affect immunological and metabolic processes^56,57^. Conversely, while some synonymous changes can affect gene regulation, they are generally thought to have less of an effect^56^. It was hypothesized in this study that substitutions like PTX3 (A22G) and PRDX2 (A51S) would decrease immunological and antioxidant activities. Additional functional confirmation of these loci is necessary^58^.

Newborn animals with diarrhea were monitored for health using the candidate gene approach. For example, CXCR1 SNPs were not significantly linked to clinical intestinal disorders in dairy calves, according to Hosseini Moghaddam et al.^59^, has demonstrated a connection between a genetic variant in the swine leukocyte antigen-DRA gene and piglet diarrhea. Additionally, Cheng et al.^60^, revealed the polymorphism of the Nramp1 gene and its correlation with pig diarrhea. Nucleotide sequence differences between healthy and afflicted kids were found by PCR-DNA sequencing of goats for the TMED1, CALR, FBXW9, HS6ST3, SMURF1, KPNA7, FBXL2, PIN1, S1PR5, ICAM1, EDN1, MAPK11, CSF1R, LRRK1, and CFH markers^61^. The immunological (SELL, JAK2, SLC11A1, IL10, FEZF1, NCF4, LITAF, SBD2, NFKB, TNF-α, IL1B, IL6, LGALS, and CATH1) and antioxidant (SOD1, CAT, GPX1, GST, Nrf2, Keap1, HMOX1, and NQO1) indicators linked to bacterial diarrhea susceptibility in Barki lambs were examined by^62^.

Transcriptome study of goat peripheral blood mononuclear cells (PBMCs) infected with the bovine viral diarrhea virus-2 revealed differential expression of immune-related genes^60^, according to the ruminant gene expression profile^63^. It was further explained that the TLR4 and downstream signalling pathways of newborn goats with diarrhea and healthy goats shared characteristics. Additionally, it was determined that the gene expression profile of diarrheal goats showed considerably higher levels of TMED1, CALR, FBXW9, HS6ST3, SMURF1, KPNA7, FBXL2, PIN1, S1PR5, ICAM1, EDN1, MAPK11, CSF1R, and LRRK1 than resistant goats^61^. Keap1, HMOX1, CMPK2, ASPG, FPGT, TNNI3 K, and LPCAT1 genes were much more highly expressed in diarrheal calves compared to resistant ones, according to Ateya et al.^64^. However, a distinct pattern was generated by the Nrf2, PRDX2, and PRDX6 genes.

The examined genes’ nucleotide sequences differed between the diarrheal and healthy calves. Gene expression analysis revealed that PTX3 was significantly up-regulated (p < 0.05) in pneumonic ewes than healthy ones^65^. Single nucleotide polymorphisms and GPX marker gene expression were linked to bacterial pneumonia in Barki sheep, according to Sayed et al.^66^.

Transmembrane protein solute carrier family 11 member 1 (SLC11A1) has been identified as one of the most well-known putative candidate genes that support innate immunity against many intracellular infections^67^. When^68^ sequenced and examined the SLC11A1 gene in Holstein and Brown, they discovered SNPs linked to mastitis susceptibility or tolerance. Compared to tolerant Holstein and Brown Swiss dairy cows, mastitic Holsteins have substantially higher levels of SLC11A1 gene expression.

CD14 has a vital role in innate immunity. According to Wright et al.^69^, the anti-bacterial peptide CD14 is one of the most important molecules that binds and neutralises bacterial endotoxins. CD14 and PRDX2 nucleotide sequence variation and expression were correlated with mastitis resistance/susceptibility in goat^70^.

In response to primary inflammatory stimuli, such as those mediated by TNFα, IL-1β, and TLR agonists, several cell types produce the glycoprotein pentraxin 3 (PTX3)^71^. The PTX3 gene is principally in charge of controlling inflammatory reactions and inherent resistance to infections, claims^72^. Additionally, it has antibacterial properties that may help shield the mammary gland from subclinical and chronic infections. PTX3, which is significantly up-regulated in the goats’ udder, is the first line of defence against S. aureus infection, according to multiple studies^73^. Single nucleotide polymorphisms (SNPs) and alterations in the gene expression profile associated with mastitis resistance/susceptibility were discovered in the PTX3 gene in the Holstein and Montbéliarde dairy cows under investigation^74^.

IRF3 belongs to the family of interferon regulatory transcription factors (IRF)^75^. Response to microbial infection by the innate immune system is significantly influenced by IRF3^76^. Individual genetic loci and MRNA levels of the IRF3 biomarker linked to pneumonia susceptibility in Baladi goats were discovered by Ateya et al.^77^.

Hydrogen peroxide can be catalyzed by the peroxiredoxin (PRDX) family of antioxidant enzyme oxidoreductase proteins due to a conserved ionised thiol. Thiol-specific peroxidase detoxifies peroxides, including sulphur, and radicals, assisting cells in defending against oxidative stress. Additionally, according to Wadley et al.^78^, it acts as a sensor for signaling events brought on by hydrogen peroxide. The PRDX6 gene was examined by Elsayed et al.^79^ as an antioxidant linked to dromedary camels’ vulnerability to trypanosomiasis.

Free radicals can be scavenged or detoxified by antioxidants, which can also stop them from generating or sequester the transition metals that cause them^80^. Glutathione peroxidase (GPX) is an example of enzymatic and nonenzymatic mechanisms that make up the body’s natural antioxidant defenses^81^.

The functions of HSP70 and HSP90 in protein folding are regulated and coordinated by the adaptor protein stress-induced phosphoprotein (STIP1)^82^. Furthermore, STIP1 is expressed in response to cellular physiological stress caused by elevated temperatures or.

additional elements^83^. In order to select for and enhance mastitis resistance in Dromedary camels^84^, integrated the nucleotide sequence variations and transcript levels of the STIP1marker.

The significant change in the pattern of immunological, and antioxidant, marker expression in diarrheal calves may be explained by the fact that damaged tissues react to free radicals more frequently than healthy ones^85^. Additionally, the intestine, which was the main site for a variety of microbes, nutrients, and immune cell interactions, was extremely susceptible to degradation^86^. The rationale may be that invasions by gastrointestinal pathogens are potent oxidizing triggers that set off immunological responses that mobilize macrophages and neutrophils to fight off invasions. This results in an excess of ROS generation and buildup, which eventually leads to oxidative stress^87^. It is clear that during bacterial infection, TLR4 and the signaling pathways it interacts with downstream are essential for inducing the production of inflammatory cytokines. Significant alterations in the mechanism controlling the gut barrier’s function are associated with diarrhea, which may increase the intestinal permeability to harmful microorganisms^88^. Additionally, ROS takes involvement in competition between microorganisms^89^. We therefore hypothesise that the diarrhea seen in these calves is mostly an infectious one. Furthermore, there is solid evidence from our real-time PCR data indicating the diarrheal calves were exhibiting a marked inflammatory response.

The diarrheal calves had significantly lower amounts of serum glucose, total protein, albumin, globulin than the healthy ones. Our findings matched with those published by^40,90,91^. Hypoglycemia in diarrheal calves may be caused by decreased glucose absorption from the damaged intestine and glucose excretion in the intestinal lumen during diarrhea, according to the available evidence^92,93^. Damage to the intestinal mucosa and increased vascular permeability may result in a protein-losing enteropathy that causes hypoproteinemia, hypoalbuminemia, and hypoglobulinemia in the diarrheal calves^94^.

When compared to control calves, the serum concentrations of triglyceride, creatinine, urea, and the activities of AST, ALT, GGT and LDH were significantly higher in the diarrheal calves. Our findings aligned with those of ^40,95^. Serum triglyceride levels have significantly increased, which may be related to poor liver function and fatty tissue lipolysis with impaired fatty acid production during infections and inflammation^96^. According to Singh et al.^97^, a decrease in renal function, a drop in glomerular filtration rate, and a decrease in urine production as a result of hypovolemia, systemic arterial hypotension, and vasopressin release may account for the elevated levels of creatinine and urea in calves with diarrhea. It may also be the consequence of the body’s proteins being catabolized under adverse conditions, which leads to an excess of urea^98^. The hemoconcentration or the spread of BVDV into extra-intestinal tissues, lamina propria, Peyer’s patches, mesenteric lymph nodes, lung, liver, kidney, and bile duct may be the cause of the markedly higher average ALT, AST, GGT, LDH concentrations in the serum of BVDV-infected calves compared to healthy calves^99^.

Since the creatine phosphokinase (CPK) enzyme is essential for maintaining tissue cells’ energy homeostasis and ensuring a steady level of ATP in the cells, elevated plasma concentrations of CPK are linked to tissue damage, poor muscle tissue reperfusion, hypoxia, exhaustion, and increased muscle membrane permeability after stress and abrupt metabolic changes. It is therefore helpful in the assessment of conditions including injury to the central nervous system, skeletal muscle, and myocardium. According to Huang et al.^100^, an increase in diarrheal calves is a sign of exhaustion, metabolic diseases, and skeletal muscle degenerations.

In order to monitor health and vitality, C-reactive protein (CRP), a diagnostic inflammatory biomarker that rises quickly in cases of inflammation or tissue destruction, binds with metabolites released from cellular degeneration to reenter the host metabolic processes so that the pathogen cannot use them. CRP elevation in diarrheal calves thus signifies pathogenic infection and tissue injury^101^.

Serum cardiac troponin I (cTn-I) levels were considerably higher in the diarrheal calves than in the healthy ones. Our findings agreed with those of^95^. Since pericarditis causes the release of cTn proteins into the bloodstream, which are normally present in blood at very low concentrations or below the limit in detection of most assays, the significant increase in cTn-I concentration in the affected group suggests myocardial cell damage^102^.

Serum cortisol levels were considerably higher in the diarrheal calves than in the healthy ones. Our results were consistent with those of^95^. When stress occurs, the primary hormone secreted to restore physiological conditions and homeostasis is cortisol. In the present investigation, diarrheal calves’ cortisol levels rose in an attempt to alleviate the stress brought on by the clinical and biochemical disruptions brought on by diarrhea^103^.

The diarrheic calves had significantly higher blood K levels and significantly lower amounts of serum Na and Cl levels than the healthy calves. Our results were consistent with those of^40,104,105^. The observed variations in serum Na, Cl, and K levels may be caused by hypovolemia, which is linked to a decrease in glomerular filtration rate, which is a major factor in the pathophysiology of hyperkalemia, as well as excessive water loss with feces, which results in dehydration and impaired cell membrane permeability^92^.

Diarrheic calves infected with BVDV also had significantly lower levels of Ca, P, Cu, Zn and Fe. The results of the present investigation were in line with those of earlier studies^105,106^. Persistent diarrhea and dehydration caused by the loss of calcium in stools may be the cause of the drop in calcium levels^98^. According to EL-dessouky et al.^107^, the decline in P was caused by more electrolyte loss than water loss. According to Palomares^108^, the notable decline in Cu, Zn, and Fe levels may be caused by a reduction in the intestinal absorption of dietary nutrients and fecal losses.

Acute phase proteins constitute an extra component of the innate immune response. These non-specific hepatic proteins are produced in reaction to cytokines that promote inflammation^109^. Diarrheic calves in this study exhibited significantly higher serum concentrations of APPs (HP, SAA and Cp). These findings were similar to those that were published by^104,110,111^. They are crucial in preserving homeostasis and biological harmony as well as regulating microbial growth until a specific immunity is established. Additionally, they possess strong anti-inflammatory, antibacterial, and antioxidant properties^112^. Moreover, APPs may enable treatment choices and serve as helpful prognostic instruments^113^.

The close correlation between gene expression and serum biochemical profiles highlights the interplay between immune activation, oxidative stress, and metabolic disturbance during diarrhea in buffalo calves. The strong association of SLC11A1 with proteins and minerals supports its role in macrophage activation and metal ion transport, while elevated correlations with cortisol and cTnI indicate systemic stress and secondary cardiac involvement^114,115^. The association of CD14 with Hp and AST indicates activation of innate immune signaling via LPS recognition, stimulating hepatic APP synthesis, while its negative correlation with Ca reflects electrolyte loss during diarrhea^116^. PTX3, IRF3, and PRDX2 showed strong correlations with CRP, GGT, LDH, and cortisol, highlighting their roles in acute-phase and oxidative defense responses^117^. The linkage of PRDX2 with CPK suggests protection against oxidative damage in muscle and liver tissues^117^. The relationship between GPX and Zn supports the trace element dependency of glutathione peroxidase activity, and the correlation of NDUFS6 with Cl implies mitochondrial adaptation to ionic imbalance during dehydration and acidosis^118^.

Although this study provides valuable insights into the molecular detection, genetic characterization, and host immune response to BVDV infection in diarrheic buffalo calves, several limitations should be acknowledged. The restricted sample size and geographic coverage may not reflect the national epidemiological status of BVDV in Egypt. The focus on BVDV alone, without screening for other enteric pathogens, limits understanding of its role in mixed infections. Future multi-regional studies with broader pathogen screening and whole-genome sequencing are needed to clarify virulence factors and enhance vaccine matching. Because only fecal samples from diarrheic calves were analyzed and paired blood samples were unavailable, the true prevalence and systemic infection status could not be fully assessed. Including both healthy and diarrheic animals in longitudinal studies integrating molecular, immunological, and biochemical analyses would enable functional validation and improve understanding of BVDV-associated diarrhea in buffalo calves.

Conclusion

The findings indicate that resistant calves and diarrheal calves differed in their genetic variants and immune and antioxidant gene expression patterns. Alterations in serum biochemical and acute phase protein markers reflected activation of innate and humoral immune responses during diarrhea. These findings suggest that genetic variations in these genes may serve as biomarkers for predicting susceptibility and guiding selective breeding for diarrhea resistance. Moreover, the sensitive detection of immune and antioxidant gene expression by real-time PCR provides a valuable reference for monitoring calf health and reducing economic losses through marker-assisted selection.

Materials and methods

Animals and study design

The study used 200 buffalo calves from several livestock farms in El-Tor, the capital of the South Sinai Governorate, which is located 265 km from the Suez Gulf in Egypt. The calves were born to one month of age. The animals had a thorough clinical evaluation utilizing the techniques outlined by^42^. Following the animals’ release, they were split up into a control group (CG) of 100 buffalo calves that appeared healthy (normal body temperatures, pulses, respiration rates, shiny eyes without discharges, normal wet muzzle and muffle, no abnormal lung sounds on auscultation, raised head, normal posture and appetite, and no lameness or diarrhea). One hundred buffalo calves in the diarrheal group (DG) experienced varying degrees of diarrhea, anorexia, emaciation, weakness, rough hair, pain, dullness, depression, pale mucus membrane, sunken eye, varying degrees of dehydration, hyperthermia, elevated pulse, and respiratory rates. To distinguish infectious from nutritional diarrhea, calves were classified using clinical, management, and laboratory criteria. Clinical data included age, rectal temperature, fecal and dehydration scores, and duration of illness. Management data covered colostrum intake, feeding type and frequency, and recent dietary changes within 72 h before onset. Laboratory analyses comprised PCR for BVDV, and where applicable, multiplex PCR or ELISA for BRV, BCV, and ETEC, fecal flotation for protozoa, and bacteriology. Serum total protein, basic biochemistry, and CBC were used to assess passive transfer and systemic effects. All methods were performed in accordance with the relevant guidelines and regulations and this study was reported in accordance with ARRIVE guidelines (https://arriveguidelines.org).

Sampling

Fecal sampling

A total of 100 fecal samples were collected from diarrheic group by placing approximately 10 g of fecal material obtained during rectal retrieval into sterilized plastic tubes. Each sample was collected using an individual glove. Following the collection process, the samples were immediately sent to a central laboratory located at the Department of Microbiology, Desert Research Center and maintained at -80 °C until using^119^. Samples yielding Ct values ≤ 30 in the BVDV classical real-time PCR were considered to have relatively high viral loads and were therefore selected for sequencing and further molecular analysis.

Blood sampling

Through jugular venipuncture, ten milliliters of blood were extracted from every animal. The samples were separated into EDTA tubes for whole blood collection and plain tubes (without anticoagulant) for serum collection. After being promptly refrigerated on crushed ice, the samples were brought to the lab. Serum samples were obtained by centrifugation in plain blood tubes at 3000 rpm for 15 min, aliquoted, and refrigerated at −20 °C for biochemical and APPs analysis, whereas whole blood was utilized for RNA extraction.

Molecular detection of bovine viral diarrhea virus (BVDV)

RNA extraction

RNA extraction was performed using the QIAamp Viral RNA Mini Kit (Qiagen, Germany). Briefly, 140 µL of the fecal suspension was mixed with 560 µL of AVL lysis buffer and 5.6 µL of carrier RNA, followed by incubation at room temperature for 10 min. Subsequently, 560 µL of 100% ethanol was added to the mixture. The samples were then washed and centrifuged according to the manufacturer’s instructions. Finally, nucleic acids were eluted in 60 µL of elution buffer provided with the kit.

Oligonucleotide primers

The primers used in this work are described in Table 1 and were synthesized by Metabion (Germany) in accordance with^120^.

PCR amplification

PCR amplification products for BVDV were analyzed by agarose gel electrophoresis to confirm the presence and size of the expected amplicons. Briefly, 5 µL of each PCR product was mixed with loading dye and loaded onto a 1.5% agarose gel prepared in 1× Tris–acetate–EDTA (TAE) buffer containing ethidium bromide (0.5 µg/mL) (or a non-toxic DNA stain). Electrophoresis was performed at 100 V for 45–60 min, and the DNA bands were visualized under a UV transilluminator. A 100 bp DNA ladder (Thermo Fisher Scientific, USA) was used as a molecular size marker. The appearance of a distinct band of the expected size (approximately 200 bp) indicated a positive result for BVDV.

Primers were utilized in a 25- µl reaction containing 12.5 µl of Quantitect probe buffer (QIAgen, Gmbh), 1 µl of each primer of 20 pmol concentration, 0.25 µl of rt-enzyme 5.25 µl of water, and 5 µl of template. The reaction was performed in a Biometra thermal cycler. Reverse transcription was applied at 50^°^C for 30 min, a primary denaturation step was done at 95^°^C for 5 min, followed by 35 cycles of 94^°^C for 30 s., annealing (55 °C for 40 s for bovine viral diarrhea virus). A final extension step was done at 72^°^C for 10 min. Fecal samples were screened for BVDV by RT-PCR targeting the 5′-UTR as described above. Additional pathogen panels (rotavirus, bovine coronavirus, enterotoxigenic E. coli (ETEC), and common protozoa) were not assayed using the same standardized molecular workflow in this study, so negative results for those agents cannot be inferred from the BVDV assay.

Gene sequencing and phylogenetic analysis

Partial sequencing of the 5′ untranslated region (5′UTR) gene for bovine viral diarrhea virus was performed using specific primers. PCR products were purified using a QIAquick PCR Product extraction kit (Qiagen, Gmbh, Germany). Sequence reactions were performed using a BigDye Terminator v3.1 Cycle Sequencing Kit (Perkin-Elmer) and purified with Centri-Sep spin columns (Thermo Fisher, Germany). The purified products were then analyzed by Sanger sequencing using an ABI 3130 Genetic Analyzer (Applied Biosystems, USA). VP60 sequences were obtained using a 3130 genetic analyzer (Applied Bio-systems, Life technologies, Thermo Fisher, Germany). Basic Local Alignment Search Tool (BLAST^®^)^121^ alignment was performed to establish sequence similarities to the sequences deposited in the GenBank database. The MegAlign (part of the Lasergene software package - Version: 12.1, URL: https://www.dnastar.com/software/lasergene/megalign-pro/) module of Lasergene DNA-Star was used to determine phylogenetic distances among the analyzed strains^122^, and MEGA6 software (Molecular Evolutionary Genetics Analysis; https://www.megasoftware.net/) was used to create a phylogenetic tree using maximum composite likelihood with 1000 bootstrap replications, neighbor-joining, and maximum parsimony^123^.

Total RNA extraction, reverse transcription and quantitative real time PCR

In accordance with the manufacturer’s recommendations, total RNA was isolated from calf blood using Trizol reagent (RNeasy Mini Ki, Catalogue no.74104). The NanoDrop^®^ ND-1000 Spectrophotometer was used to quantify and qualify the amount of isolated RNA. Each sample’s cDNA was created in accordance with the manufacturing process (Thermo Fisher, Cat-alog no, EP0441). Using quantitative RT-PCR with SYBR Green PCR Master Mix (2x SensiFastTM SYBR, Bioline, CAT No: Bio-98002), the gene expression patterns for coding segments of genes encoding immunity (SLC11A1, CD14, PTX3, and IRF3) and antioxidant (PRDX2, PRDX6, GPX, ST1P1) were evaluated. Via real-time PCR with the SYBR Green PCR Master Mix (Quantitect SYBR green PCR kit, Catalogue no. 204141), the relative mRNA level was measured.

Primers were created based on the Bubalus bubalis sequence that was published in PubMed, as indicated in Table 6. As a constitutive control for normalisation, the housekeeping gene GAPDH was employed. The reaction mixture, which had a total volume of 25 µl, contained 3 µl of total RNA, 4 µl of 5x Trans Amp buffer, 0.25 µl of reverse transcriptase, 0.5 µl of each primer, 12.5 µl of 2x Quantitect SYBR green PCR master mix, and 8.25 µl of RNase-free water. After putting the finished reaction mixture in a thermal cycler, the following procedure was run: reverse transcription for 30 min at 50 °C, primary denaturation for 10 min at 94 °C, 40 cycles of 94 °C for 15 s, annealing temperatures for 1 min as indicated in Table 5, and 72 °C for 30 s. A melting curve analysis was conducted at the conclusion of the amplification step to verify the PCR product’s specificity. Using the 2 − ΔΔCt technique, the relative expression of each gene per sample was compared to that of the GAPDH gene^124^.

Table 6. Forward-reverse oligonucleotide-based real-time PCR primers for the immunological and antioxidant genes being studied.Investigated markerPrimerProduct size (bp)Annealing temperature (°C)GenBank isolateOrigin SLC11A1 F5′- ACTCGCTCCTGTGCCATCCTG − 3R5′- CTTCTCCTGATCCTCTTCAGGA-3′42960FJ827149.1 CD14 F5′- CAGTTGCGACATCTGGACCTC − 3R5′- AGTGTCATATACAATGAAAGCAT − 3′36060DQ457089.1Present research PTX3 F5′- GACGAGCTGCAGAAGCTGCGG − 3′R5′- TGCAGGCGCTGAAAGTCTCGAG − 3′38858XM_006054085.4 IRF3 F5′- CCTCGGATACTGCCCTGGCTGA-3′R5′- TCAAGTCCATGTCACTCAGTAAC − 3′43058XM_025270005.3 PRDX2 F5′- CAAGTTCGTGCATCCGAGAGTC − 3′R5′- TCATCTTCCTTCAGCACGCCATA- 3′42558XM_006041572.4 PRDX6 F5′- GGAGGTCTCCTCCTCGGGGACG − 3′R5′- AATCTCATCAAAGTTCCTGCCAG − 3′47358MH085038.1 GPX F5′- TGCGAGGTGAATGGCGAGAAGGC- 3′R5′- CTAGGCAGAGGCCCCCTGGGACA − 3′26758JN801165.1 ST1P1 F5′- TGAGTGCCGGCAACATTGACGA − 3′R5′- AGGTCGGACGGCTTGTTCCGCA − 3′45460XM_006050858.3 GAPDH F5′- GGCAAAGTGGACATCGTCGCCA-3′R5′- AGCCTTCTCCATGGTAGTGAAG − 3′24958AY974798.1SLC11A1: Solute Carrier Family 11 Member 1; CD14: Cluster of Differentiation 14; PTX3: Pentraxin 3; IRF3: Interferon Regulatory Factor 3; PRDX2: Peroxiredoxin 2; PRDX6: Peroxiredoxin 6; GPX : Glutathione Peroxidase; ST1P1: stress-induced phosphoprotein 1; GAPDH: Glyceraldehyde-3-Phosphate Dehydrogenase.

DNA sequencing and polymorphism detection

Removal of primer dimmers, nonspecific bands, and other contaminants was done prior to DNA sequencing. As described by Fonseca-Benitez et al.^125^, PCR purification kit was used in accordance with the manufacturer’s instructions to purify real-time PCR products with the desired size (target bands) (Jena Bioscience # pp-201×s/Germany). The Nanodrop (Uv-Vis spectrophotometer Q5000/USA) was used to quantify the PCR product in order to produce high-quality results and guarantee sufficient concentrations and purity of the PCR products^126^. PCR results containing the target band were sent for forward and reverse DNA sequencing using an ABI 3730XL DNA sequencer (Applied Biosystem, USA) in order to identify SNPs in genes examined in control and diarrhea -affected calves. This was done using an enzyme-chain terminator technique created by^127^. Chromas 1.45 and blast 2.0 tools were used to analyse the DNA sequencing data^121^. PCR results of the genes under investigation and reference sequences found in GenBank were compared, and differences were categorized as single-nucleotide polymorphisms (SNPs). Based on DNA sequencing data alignment, the MEGA6 software (Molecular Evolutionary Genetics Analysis; https://www.megasoftware.net/) was used to compare the amino acid sequences of the genes under investigation among the enrolled calves^128^.

Biochemical analysis

In accordance with the author’s guidelines, the obtained serum samples were used to evaluate the following parameters: serum concentration of total protein, glucose and cholesterol (Gamma Trade Company, Egypt); triglyceride, calcium (Ca), phosphorus (P), potassium (K), chloride (Cl), sodium (Na), Copper (Cu), iron (Fe), zinc (Zn), (Spinreact Company, Spain); aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT), lactate dehydrogenase (LDH), (Spectrum Company, Egypt); creatine phosphokinase (CPK) was determined by the method of^129^. Total protein, albumin, glucose, cholesterol, and urea (Gamma Trade Company, Egypt); Chemiluminescence immunoassay (CLIA) kits supplied by Diasorin^®^ (Saluggia, Italy) were used for serum cortisol. Cardiac troponin I (cTnI) was measured using an ELISA kit (FLUOstar Omega, USA). In addition, serum cortisol and C-reactive protein (CRP) concentrations were determined using ELISA kit (Eucardio Laboratory, Inc., Encinitas, and CA., U.S.A.). Globulin was calculated by subtracting albumin values from total serum protein. Serum haptoglobin (Hp) by Eagle Biosciences (Columbia) ELISA kits; serum amyliod A (SAA) concentrations by IBL International Crop (canda)^®^ ELISA kits; and serum caeruloplasmin (Cp) levels by Arbor Assays DetectX ^®^ (USA)^®^ kits.

Statistical analysis

Statistical analysis was performed using SPSS software (Statistical Package for the Social Sciences, version 23; IBM Corp.; https://www.ibm.com/products/spss-statistics. An independent-samples t-test was used to compare the investigated groups. The data observed in each group were tested for normality using the Kolmogorov-Smirnov test and all parameters were not statistically significant which indicate that data are parametric (normally distributed), so the results were expressed as mean ± SD. Difference in the frequencies of each gene SNPs between diarrheic and healthy calves was statistically assessed using Chi-square test to match the distribution of the recognized SNPs among the two groups using SPSS version 23, USA. A Linear Discriminant Analysis (LDA) was conducted to determine whether gene-level SNP averages could differentiate between diarrheic and healthy calves. The 8 gene average scores served as predictor variables, and the health status (diarrheic vs. healthy) was the grouping variable Statistical consequence was established at p < 0.05. A significance level of P < 0.05 was established. In order to evaluate the relationship between the gene expression and serum profile of biochemical and APPs markers in the diarrheic buffalo calves, Pearson correlation was used. Consideration was given to the P value and correlation coefficient (r). P < 0.05 was used to determine statistical significance for the results.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1