Introduction

Canine hepatozoonosis is a prevalent canine vector-borne disease (CVBD) caused by Hepatozoon canis infection in dogs1. The clinical presentation of this disease varies significantly, ranging from asymptomatic to severe cases. Symptoms are often nonspecific and may include anemia, fever, lethargy, and anorexia2. The severity of the disease is closely linked to the level of parasitemia in affected dogs3. H. canis has a broad geographical distribution and is reported worldwide4. Its detection can be performed through various diagnostic techniques. Conventional microscopic examination involves identifying intracellular “isogamonts” or “capsule-like shaped gametocytes” in neutrophils or monocytes5. Molecular detection methods, such as conventional polymerase chain reaction (cPCR) and real-time PCR, are also widely used for identifying H. canis DNA6,7,8. Additionally, serological techniques like the indirect fluorescent antibody test (IFAT) and enzyme-linked immunosorbent assay (ELISA) are employed for diagnosis9,10. Despite the availability of these diagnostic methods, each has limitations, including cost inefficiency, time consumption, and the requirement for skilled personnel. Considering these challenges, small peptide biomarkers or biomarker panels may offer a promising alternative for improved and efficient detection of H. canis infection.

Peptide biomarkers, which are small fragments of proteins, are key components of biomarker panels. These peptides can be found in various biological samples such as serum, saliva, cerebrospinal fluid, and urine11,12,13,14. Although peptides are smaller than proteins, they play significant roles in both normal physiological and pathophysiological processes. Some notable functions of peptides include acting as hormones, signaling molecules, neurotransmitters, and regulators of biological processes15. The advantage of peptidomic analysis lies in its ability to reveal the regulation and interactions of proteins and peptides within complex biological pathways and networks. Compared to DNA-based molecular techniques, peptidomic analysis provides a clearer understanding of dynamic changes in peptide and protein expression levels in response to various stimuli, diseases, or treatments16,17. Recent studies have employed proteomic analysis to identify biomarker panels in various areas of veterinary parasitology. Examples include proteomic analysis of Babesia canis infection in dogs18, proteome profiling of lymphatic filarial worms19, and proteomic analysis of Toxocara canis and T. cati20. Although peptidomic analysis has shown potential in various fields, its application in veterinary parasitology remains limited. In particular, serum peptidome analysis of canine hepatozoonosis, specifically focusing on H. canis, has yet to be fully explored.

The primary objective of this study is to identify peptide mass fingerprints (PMFs), serum peptidome clusters, and potential candidate peptides that may serve as novel biomarker panels for detecting H. canis infection. To achieve this, we aim to utilize matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) combined with liquid chromatography-tandem mass spectrometry (LC–MS/MS) for comprehensive serum peptidome profiling.

Materials and methods

Ethics approval

All procedures conducted in this study were reviewed and approved by the Chulalongkorn University Animal Care and Use Committee under protocol number 2431057. Additionally, all biosafety procedures were approved by the Faculty of Veterinary Science Biosafety Committee (IBC) at Chulalongkorn University, with reference number 2431026.

Fig. 1
figure 1

Flowchart illustrates the processes of sample collection, parasite confirmation, and the complete serum peptidome analysis conducted in this study.

Full size image

Study design

The flowchart and overall study design are summarized in Fig. 1, with detailed methodologies for each step described in the following sections. This study is performed in accordance with relevant guidelines and regulations. All methods are reported in accordance with ARRIVE guidelines.

Animals and serum collection process

Blood and serum samples were collected from dogs (Canis lupus familiaris) for this study. The sample collection process was conducted by Licensed veterinarians at private veterinary clinics and animal hospitals in Bangkok and surrounding areas, Thailand, between January and December 2022. The collected samples were categorized into two groups: the H. canis-infected group (n = 15) and the healthy control (non-infected) group (n = 20). For each dog, 1 mL of blood was collected in an ethylenediaminetetraacetic acid (EDTA) tube for parasite confirmation, while an additional 2 mL of blood was drawn into a non-coagulant or no-additive tube for serum collection.

All blood samples collected in non-coagulant tubes were processed by centrifugation at 5000 RPM at 4 °C for 10–15 min. The supernatant, representing the serum fraction, was carefully collected. Each serum sample was then individually separated and aliquoted into 100 µL volumes in microtubes. The aliquoted serum samples were stored at −20 °C until further analysis for serum peptidome profiling.

Parasite confirmation

All EDTA blood samples were collected and tested to confirm H. canis single infection using both microscopic and molecular methods at the Vet Central Laboratory. The microscopic examination was conducted using the buffy coat smear technique, following established protocols described by O’Dwyer, da Silva and Madeira21. EDTA blood samples were collected from dogs for analysis. Blood smears were prepared, air-dried, and fixed with absolute methanol for 3 min. The smears were then stained with Wright-Giemsa solution for 10 min. The presence of ellipsoidal-shaped isogamonts observed under a light microscope was considered indicative of H. canis infection using the microscopic technique. For molecular confirmation, conventional polymerase chain reaction (cPCR) was performed following established protocols from Perkins and Keller22. Briefly, H. canis infection was confirmed using primers targeting the partial 18 S rRNA gene. A forward primer specific for hemogregarines (HEMO1: 5′-TAT TGG TTT TAA GAA CTA ATT TTA TGA TTG-3′) and a reverse primer specific for apicomplexan parasites (HEMO2: 5′-CTT CTC CTT CCT TTA AGT GAT AAG GTT CAC-3′) were employed. The PCR reaction was carried out in a 20 µL reaction mixture containing 2 µL of DNA template, 1X GoTaq® Green Master Mix (Promega, USA), 0.2 mM of each primer, and nuclease-free water. The amplification process was conducted using a thermal cycler (BIOER Technology, China). A positive control for H. canis DNA was included, obtained from a naturally infected dog in a previous study23. Nuclease-free water was used as a negative control. The PCR reaction successfully amplified a 900 bp product. The PCR products were stained with RedSafe™ Nucleic Acid Staining Solution (INtRON Biotechnology, Korea) and analyzed using 1% agarose gel electrophoresis. A 100 bp DNA ladder (SibEnzyme®, Russia) served as the molecular size marker for determining the product’s molecular mass. The PCR products were subsequently purified using the NucleoSpin® Gel and PCR Clean-up Kit (MACHEREY-NAGEL, Germany).

In order to exclude other Canine Vector Borne Diseases (CVBDs), including Babesia spp., Anaplasma platys, Ehrlichia canis, Mycoplasma spp., Filarial nematodes, and Trypanosoma spp., all samples from two groups were subjected to conventional polymerase chain reaction (cPCR) using different primers, product sizes, target genes, and references, which are documented in supplementary Table 3.

Analysis of serum peptide barcode by MALDI-TOF-MS

Each serum sample was purified using a Ziptip C18 column (Millipore, Burlington, MA, USA). The Ziptip C18 column was initially wetted with 100% acetonitrile (ACN) and equilibrated with 0.1% trifluoroacetic acid (TFA). Each serum sample was acidified with 0.1% TFA before aspirating five times through the Ziptip C18 column to ensure peptide binding to the C18 resin. The bound peptides were subsequently eluted with 20 µL of 100% ACN. The total peptide concentration in the samples was measured using the Bradford assay, with bovine serum albumin (BSA) as the protein standard24.

The concentration of all serum samples was adjusted to a final concentration of 0.25 µg/µL using 0.1% trifluoroacetic acid (TFA). Subsequently, the serum samples were mixed with the MALDI matrix solution, which consisted of 2.5% TFA and 10 mg/mL α-cyano-4-hydroxycinnamic acid dissolved in 50% acetonitrile (ACN) at a 1:1 ratio. One microliter of the prepared serum peptidomes was directly spotted onto the MALDI target plate (MTP 384 ground steel, JEOL, Japan) and allowed to air dry at room temperature. MALDI-TOF MS spectra were acquired using the JMS-S3000 SpiralTOF™-plus (JEOL, Japan) in Linear positive mode, covering a mass range of 1,000–10,000 Da. For each sample, a 50 Hz laser was used to accumulate 500 shots. For external calibration, the ProteoMass Peptide & Protein MALDI-TOF MS Calibration Kit (Sigma-Aldrich, St. Louis, MO) was employed. The calibration kit included human angiotensin II (m/z 1046), P14R (m/z 1533), human adrenocorticotropic hormone fragment 18–39 (m/z 2465), bovine insulin oxidized B-chain (m/z 3465), bovine insulin (m/z 5731), and cytochrome c (m/z 12362).

Serum peptidome analysis using liquid chromatography tandem mass spectrometry (LC-MS/MS)

The peptides from each serum sample were pooled and prepared for injection into an Ultimate3000 Nano/Capillary LC System (Thermo Scientific, UK) coupled with a hybrid quadrupole Q-Tof impact II™ (Bruker Daltonics).In brief, one microliter of peptide solution was enriched on a µ-Precolumn (300 μm i.d. x 5 mm) packed with PepMap 100 resin (5 μm, 100 Å, Thermo Scientific, UK). Subsequent peptide separation was performed on a 75 μm I.D. x 15 cm analytical column packed with Acclaim PepMap RSLC C18 resin (2 μm, 100 Å, nanoViper, Thermo Scientific, UK). The C18 column was housed in a thermostatted column oven maintained at 60 °C. A gradient elution was applied using solvent A (0.1% formic acid in water) and solvent B (0.1% formic acid in 80% acetonitrile). Over 30 min, the peptides were separated with a gradient of 5–55% solvent B at a flow rate of 0.30 µL/min. Electrospray ionization was carried out using CaptiveSpray at 1.6 kV. The drying gas was nitrogen, with a flow rate of approximately 50 L/h. Nitrogen gas was also employed as the collision gas to generate collision-induced dissociation (CID) product ion mass spectra. In positive-ion mode, mass spectra (MS) and MS/MS spectra were acquired at 2 Hz across the m/z range of 150–2200. Collision energy was adjusted to 10 eV depending on the m/z value. Each serum sample underwent triplicate LC-MS analysis to ensure reproducibility and accuracy.

MaxQuant version 2.5.0.0 was used to quantify and analyze the proteins in individual samples. The MS/MS spectra were correlated with the Uniprot Canis lupus familiaris database using the Andromeda search engine25. MaxQuant’s standard settings for label-free quantification were applied, with unspecific digestion mode. Oxidation of methionine and acetylation of the protein N-terminus were included as variable modifications. The parameters allowed for a mass tolerance of 0.6 dalton for the main search. For protein identification, only peptides with a minimum of seven amino acids and at least one distinct peptide was required. Proteins needed to include at least two peptides, with one being unique, to be recognized and included in further data analysis. Reversed search sequences were employed to estimate the protein false discovery rate (FDR), which was set at 1%. A maximum of five modifications per peptide was permitted. The protein sequences from the Canis lupus familiaris proteome were obtained from the UniProt database as a FASTA search file (February 1, 2025). Mass intensities were log2-transformed, and missing values were imputed in Perseus26 using a constant value of zero.

Peptidome bioinformatic analysis

The visualization and statistical analyses of the LC-MS data were conducted using the web-based bioinformatics tool “MetaboAnalyst” version 6.027. This included orthogonal partial least squares discriminant analysis (orthogonal PLS-DA) modeling, as well as differential analysis methods such as volcano plot and heatmap visualization. A significance threshold of p-value < 0.05 was applied. Potential functional interaction networks between identified proteins and small compounds were analyzed using the STITCH database version 5.028.

Results

Serum peptide mass fingerprint among Hepatozoon canis infected dogs and healthy dogs

Fifteen serum samples from the H. canis-infected group and twenty from healthy control dogs were subjected to peptide profiling using MALDI-TOF MS. The results revealed a significant difference in peptide mass fingerprints between the infected and control groups (Fig. 2A). Peptide mass fingerprint analysis indicated that the H. canis-infected group tended to display peptide distribution predominantly in the m/z range of 1,000 to 3,500 Da, whereas the control group showed peptide aggregation primarily between m/z 3,500 to 6,000 Da. The serum peptide profiles were then subjected to statistical evaluation using Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA). The OPLS-DA model demonstrated clear separation between the infected and control groups, suggesting the presence of distinct peptide candidates differentiating the two conditions (Fig. 2B). Peptide mass fingerprinting and Orthogonal PLS-DA analysis from MALDI-TOF MS revealed distinct peptide patterns capable of differentiating between the H. canis-infected and control groups. A volcano plot was generated to highlight the most promising peptide masses between the two groups, identifying candidates with a p-value < 0.05 and a fold change > 2.0 (Fig. 2C). Additionally, variable importance in projection (VIP) score analysis identified the top 40 candidate peptide masses with VIP scores exceeding 2.0, as illustrated in Fig. 2D. Five significantly elevated peptides were observed in the H. canis-infected group at m/z values of 1423.79, 1495.25, 2837.65, 2874.76, and 2892.06. These peptides were identified as follows: AGTGEQGLLNAYCK (FERM domain-containing protein 8 or FRMD8), LLEFLSSFQKER (Calcium binding protein 39-like or CAB39L), NNAGFRVWVLFFLVMCSFSLLFLD (Syntaxin-18 or STX18), HEPLVLFCESCDTLTCRDCQLNAHK (Tripartite motif-containing 28 or TRIM28) and GEEATFQISGLQTNTDYRFRVCVCR (Fibronectin type III domain-containing 3B or FNDC3B). Further details regarding these peptides are provided in Table 1.

Therefore, the MALDI-TOF MS results demonstrated distinct peptide mass fingerprints (PMFs) specific to the H. canis-infected group and identified significantly different peptide masses between the two groups. Subsequently, LC-MS/MS was employed to identify and characterize the serum peptide biomarkers in greater detail.

Fig. 2
figure 2

The serum peptidome data obtained from MALDI-TOF MS were used to screen peptide profiles and generate peptide mass fingerprints (PMFs) (A). The average mass spectra ranged from m/z 1,000 to 6,000. The upper panel displays spectra from Hepatozoon canis-infected dogs, while the lower panel represents healthy controls. The accompanying color scale indicates peptide concentration levels, with red representing higher and blue representing lower abundance (B). The Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) demonstrated clear separation between the infected and control groups (C). The volcano plot analysis revealed peptide masses with statistically significant differences (p < 0.05) and fold changes greater than 2.0 between the two groups (D). The Variable Importance in Projection (VIP) score analysis identified the top 40 candidate peptides, each with a VIP score exceeding 2.0, indicating their strong contribution to group differentiation based on MALDI-TOF MS data.

Full size image

The analysis of differentially expressed peptides tandem using liquid chromatography mass spectrometry (LC-MS/MS)

In this study, LC-MS/MS was employed to identify potential peptide candidates differentiating the H. canis-infected group from the control group. A total of 32,355 peptides were detected from the serum samples. Heatmap analysis was performed to visualize differences in peptide intensity between the two groups, with color values ranging from − 1.5 to 3.3. The heatmap (Fig. 3A) revealed distinct expression patterns of several candidate peptides. Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) demonstrated clear discrimination of peptide patterns (Fig. 3B). VIP score analysis identified the top 40 peptides contributing to group separation, each with a VIP score greater than 2.0 (Fig. 3C). Volcano plot analysis (Fig. 3D) applying a p-value threshold of < 0.05 and a fold change > 2.0, revealed 7,891 differentially expressed peptides—comprising 12 significantly downregulated and 7,879 significantly upregulated peptides in the H. canis-infected group (Fig. 3D). The top 98 selected upregulated peptides and 12 downregulated peptides are presented in Supplementary Tables 1 and 2, respectively.

Fig. 3
figure 3

The LC-MS/MS analysis revealed a set of candidate peptides differentiating the H. canis-infected group from the control group (A). Heatmap analysis illustrated peptide expression patterns between groups, where red columns represent control samples and green columns represent infected samples. Each row corresponds to a unique peptide detected by LC-MS/MS, with color intensity indicating relative peptide abundance. Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) demonstrated clear separation between the two groups, highlighting distinct peptide expression profiles (B). Variable Importance in Projection (VIP) analysis identified the top 40 candidate peptides with VIP scores exceeding 2.0 (C). Volcano plot analysis identified differentially expressed peptides in the infected group compared to controls, including significantly upregulated, downregulated, and non-significant peptides (D). Notable candidates included PLEC (plectin), CHD7 (DNA helicase), THBS1 and THBS4 (thrombospondins), LRP2 and EGF-like domain-containing proteins, KMT2C (histone methyltransferase), EXPH5 (RabBD domain protein), Attractin-like 1, CENPF (centromere protein F), ZEB2 (zinc finger E-box binding protein), TNXB (tenascin XB), laminin subunits (LAMA5, gamma 1 and gamma 3), DMD (dystrophin), FBN2 and FBN3 (fibrillins), JAG1 (Delta-like protein), AQR (RNA helicase), GPATCH8, UBR5 (E3 ubiquitin ligase), ANK3 (ankyrin 3), and Stabilin 2.

Full size image

Peptide identification and network analysis of candidate peptides

Following LC-MS/MS analysis, 98 peptides were selectively identified from the upregulated group based on volcano plot and VIP score results. These candidate peptides were further analyzed using the STITCH bioinformatics platform to explore potential interactions between proteins and chemical compounds. The resulting interaction network revealed that several of these peptides were associated with commonly used antiprotozoal and antibiotic drugs for treating canine hepatozoonosis. These included doxycycline, imidocarb dipropionate, sulfamethoxazole, trimethoprim, sulfadiazine, clindamycin, decoquinate, pyrimethamine, ponazuril, oxytetracycline, tetracycline, primaquine, chloroquine, toltrazuril, amprolium, azithromycin, diminazene aceturate, atovaquone, and minocycline.

Table 1 Potential candidate peptides information among upregulated peptide in Hepatozoon canis infected group.
Full size table
Fig. 4
figure 4

The protein–chemical drug interaction network was generated using the STITCH bioinformatics tool based on the 98 selected upregulated peptides identified between the two groups. In the network, proteins are represented as nodes, while oval-shaped nodes denote chemical reagents or drugs. The thickness of each connecting line indicates the strength of the interaction. Green lines represent peptide–drug interactions, red lines indicate drug–drug interactions, and gray lines show peptide–peptide associations. Highlighted circles indicate the key candidate peptides identified as noteworthy in this study.

Full size image

Among the top 98 upregulated peptides identified from a total of 7,880 in the H. canis-infected group, all were carefully selected for STITCH analysis. The study highlighted two notable peptides ZEB2 (Zinc finger E-box binding homeobox 2) and TNS1 (Tensin 1) which exhibited moderate associations with doxycycline, a commonly used treatment for H. canis infection29.

TNS1 also showed moderate interactions with mTOR (mechanistic target of rapamycin) and MAST4 (microtubule-associated serine/threonine kinase family member 4), and weak associations with predicted functional partners including RPTOR (Regulatory-associated protein of mTOR, complex 1), EIF4EBP1 (eukaryotic translation initiation factor 4E-binding protein 1), and RPTOR complex 2 components. MTOR itself demonstrated strong connections with six predicted partners: RICTOR, AKT1S1, RHEB, EIF4EBP1, MLST8, and RPTOR all forming a tightly interconnected network. In the case of ZEB2, a moderate peptide-peptide interaction was observed with ITGA2B (Integrin alpha-IIb). ITGA2B, in turn, showed strong associations with six other peptides: LAMA2 (laminin alpha-2), LAMA5 (uncharacterized laminin alpha-5), THBS1 and THBS4 (thrombospondins), ITGB3 (integrin beta-3), and TNXB (tenascin XB), along with a weaker interaction with FBN2 (fibrillin 2).

Interestingly, Acetyl-CoA was identified as a predicted functional partner that exhibited several strong peptide-drug interactions with upregulated peptides, including ACACA (acetyl-CoA carboxylase alpha), TAF1 (TATA-box binding protein-associated factor 1), CENPF (centromere protein F), and CHD3 (chromodomain helicase DNA-binding protein 3). Notably, CHD3 also demonstrated a moderate peptide-peptide interaction with one of the candidate peptides, THBS1 (thrombospondin 1). Additionally, various peptide-peptide interactions, drug–peptide associations, and non-interacting nodes linked to signaling pathways were identified (see Fig. 4). From these networks, 14 peptides were highlighted as key candidates due to their direct or indirect interactions with common H. canis treatment drugs or their association with predicted functional partners, as listed in Table 1. Furthermore, the full List of all 98 rigorously selected upregulated peptides, along with their corresponding names and sequences, is provided in Supplementary Table 1.

Discussion

This study is the first to apply serum peptidomic profiling using MALDI-TOF MS and LC-MS/MS to investigate canine hepatozoonosis. Our findings revealed distinct peptide mass fingerprints (PMFs) that effectively differentiated infected dogs from healthy ones. Among the 98 significantly upregulated peptides, several candidates including ZEB2, TNS1, and mTOR showed predicted associations with commonly used antiparasitic drugs, such as doxycycline and azithromycin, suggesting both diagnostic and therapeutic relevance.

MALDI-TOF MS enables the detection of peptides and proteins within biological samples by generating PMFs. These fingerprints can be used to identify potential protein candidates or biomarker panels by comparing disease and control samples30. MALDI-TOF MS has been widely employed to identify peptide mass fingerprints across various fields, particularly for detecting diseases and abnormalities in both human and veterinary medicine31.

The solid-phase extraction with C18-ZipTips was used because it’s a well-established and effective method for preparing samples for MALDI-TOF MS profiling. This technique, based on reversed-phase chromatography, efficiently removes abundant proteins and desalt samples, which are both crucial for reproducible MS results32. The robustness and reliability of MALDI-TOF MS combined with ZipTip are widely supported by numerous studies on protein-peptide profiling33,34,35,36,37. In this study, serum samples were acidified using 0.1% TFA before aspiration through the ZipTip C18 column, as detailed in the Materials and Methods section. This acidification step is critical for effective peptide extraction and mitigating potential issues with larger proteins or lipids.

In this study, MALDI-TOF MS was employed to generate PMFs for distinguishing between H. canis-infected dogs and healthy controls. The results demonstrated that the PMFs patterns from the infected group were clearly distinguishable from those of the control group. These findings suggest that MALDI-TOF MS may serve as a promising diagnostic tool for differentiating between infected and non-infected cases.

Although no prior studies have applied MALDI-TOF MS specifically to canine hepatozoonosis, our results align with findings from other studies involving protozoan detection in veterinary medicine38 for example Leishmania spp39., Giardia spp40., Trypanosoma spp41. A previous related study on Plasmodium falciparum, an intracellular parasite that infects both humans and animals, demonstrated the use of MALDI-TOF MS to distinguish between Plasmodium-infected and uninfected Anopheles mosquitoes. The analysis revealed over ten peptide mass intensities capable of differentiating between the two group42. Our peptide mass fingerprinting results support previous findings suggesting that MALDI-TOF MS holds promise as a rapid and direct diagnostic tool for screening canine hepatozoonosis.

However, while MALDI-TOF MS provides mass intensity data for peptides, it does not offer peptide identification or quantification. Therefore, LC-MS/MS was employed in this study to accurately detect and quantify potential peptide biomarkers.

In contrast to MALDI-TOF MS, LC-MS/MS is widely utilized for both peptide identification and quantification. It offers higher sensitivity and resolution by detecting a broader range of compounds with varying ionization efficiencies, and ability to generate multiple charged ions43. This study identified the top five potential peptide masses from MALDI-TOF MS (m/z 2892.06, 2837.65, 2874.76, 1495.25, and 1423.79), which were predominantly observed in the serum of H. canis-infected dogs. LC-MS/MS analysis confirmed five of these masses as significantly upregulated in the infected group, consistent with MALDI-TOF MS results. These corresponded to peptide sequences from key proteins: FNDC3B (Fibronectin type III domain-containing protein 3B), STX18 (Syntaxin-18), TRIM28 (Tripartite motif-containing protein 28), CAB39L (Calcium binding protein 39-like), and FRMD8 (FERM domain-containing protein 8). While the physiological relevance of these peptides remains unclear in canines, previous studies in human medicine have characterized several of them44,45,46,47,48. However, the remaining five candidate peptides were not detected at notable levels during LC-MS/MS analysis.

Consequently, LC-MS/MS was utilized to identify peptide biomarker panels aimed at enhancing the sensitivity of diagnostic approaches for canine hepatozoonosis. In this study, we identified key candidate peptides predominantly expressed in the H. canis-infected group. A total of 98 upregulated peptides were further analyzed using the STITCH database to explore peptide-drug interaction networks. Among the 98 upregulated peptides, 37 showed peptide-peptide associations, while only three ZEB2 (Zinc finger E-box binding homeobox 2), TNS1 (Tensin 1), and mTOR (mechanistic Target of Rapamycin) demonstrated moderate interactions with doxycycline and mTOR. Based on the network analysis, we proposed four peptides TNS1, ZEB2, MAST4, and MTOR as key biomarker candidates due to their direct interactions within the network. Nonetheless, the remaining peptides may also serve as co-biomarkers to aid in distinguishing H. canis-infected dogs from healthy controls (Fig. 4 and Supplementary Table 1).

Several commonly used drugs for the treatment of canine hepatozoonosis, including infections caused by H. canis and H. americanum, have been reported in previous studies. These include doxycycline29,49, imidocarb dipropionate29,50,51,52,53, sulfamethoxazole54, trimethoprim54,55,56, sulfadiazine55, clindamycin52,56, decoquinate56, pyrimethamine56, ponazuril57, oxytetracycline58, tetracycline51, toltrazuril50,52,54. Additionally, antimalarial drugs used against Plasmodium spp., such as primaquine59 and chloroquine60, as well as anticoccidial agent like amprolium61, and drugs commonly used to treat canine babesiosis including azithromycin62,63, diminazine aceturate62, atovaquone62,63 and minocycline62 were include. The integration of bioinformatics tools, particularly STITCH network analysis, enabled functional exploration of peptide-drug and peptide-peptide interactions, offering valuable insight into host-pathogen dynamics and potential biological pathways involved in disease progression. These findings provide a solid framework for the development of peptide-based diagnostic assays and a deeper understanding of protozoal infections in veterinary medicine (Fig. 4).

ZEB2 (Zinc finger E-box binding homeobox 2), also known as SIP1, is part of the Zfh1 family and plays a key role in epithelial-to-mesenchymal transition. While its involvement in various human cancers is well documented64,65, recent studies have also linked ZEB2 to canine mammary tumors66. Our findings support its potential as a diagnostic marker and its predicted association with doxycycline, suggesting further investigation is warranted.

Additionally, in the STITCH network analysis, ZEB2 was found to exhibit a mild interaction with its predicted functional partner, ITGA2B (integrin alpha-IIb, 1085 amino acids). ITGA2B encodes a protein that plays a critical role in platelet aggregation and blood clot formation in dogs. Particularly, mutations in the ITGA2B gene have been linked to Type I Glanzmann’s thrombasthenia in a Great Pyrenees dog67. Although there is only one report suggesting a connection between ZEB2 and ITGA2B and it does not describe a direct interaction both proteins are known to participate in processes related to cell adhesion and migration68.

TNS1 (Tensin-1), another promising peptide identified, is involved in focal adhesion and cell signaling. Altered expression of TNS1 has been observed in several human cancers, including gastric, breast, and colorectal cancer69. Although current evidence for its interaction with doxycycline is limited, our results indicate a potential role in canine disease models that merits further study.

Although the STITCH database indicated a weak interaction between doxycycline and TNS1 (Tensin-1), direct studies or concrete evidence supporting a relationship between doxycycline and Tensin-1 peptides remain limited and not well-characterized. Dixon et al. developed a tubuloid model from an inducible Pkd2 knockout system (Pkd2fl/fl Pax8rtTA TetOCre + mTmG), allowing for the tracking of morphological, protein, and genetic changes associated with cyst formation. In this model, doxycycline was used to activate Cre recombinase, leading to deletion of the floxed Pkd2 gene in kidney cells. Interestingly, TNS1 expression was reported to be significantly reduced in human autosomal dominant polycystic kidney disease (ADPKD) tissues compared to normal kidney tissue70. However, this study did not establish a direct interaction between doxycycline and Tensin-1. Therefore, despite the STITCH network suggesting two potential peptide-drug interactions involving ZEB2 and TNS1 with doxycycline, the evidence for these interactions remains indirect and requires further investigation.

mTOR (mechanistic target of rapamycin), a serine/threonine kinase, regulates essential cellular processes such as growth, proliferation, and survival. Dysregulation of mTOR has been implicated in multiple canine cancers71, including osteosarcoma72 and canine mammary carcinoma73,74. Our analysis demonstrated a strong predicted interaction between mTOR and azithromycin, aligning with studies in human CD4 + T cells where azithromycin modulated mTOR signaling75,76,77,78. This suggests a potential immunomodulatory role for mTOR-associated peptides in the pathogenesis of canine hepatozoonosis76.

While azithromycin is commonly used to treat canine babesiosis, its role in managing H. canis infections remains unexplored62,79. The predicted mTOR-azithromycin interaction identified in our study warrants future investigation into its potential therapeutic application in canine hepatozoonosis.

This study represents the first application of serum peptidomic profiling using MALDI-TOF MS and LC-MS/MS to investigate H. canis infection in dogs. Our findings revealed distinct peptide mass fingerprints that effectively differentiated infected from healthy dogs. Among the 98 significantly upregulated peptides, several candidates including ZEB2, TNS1, and mTOR demonstrated predicted associations with commonly used antiparasitic drugs, such as doxycycline and azithromycin, suggesting both diagnostic and therapeutic relevance. The integration of bioinformatics tools, particularly STITCH network analysis, enabled exploration of functional peptide-drug and peptide-peptide interactions, revealing insights into host–pathogen dynamics and potential pathways involved in disease progression. These results provide a promising foundation for the development of peptide-based diagnostic assays and a deeper understanding of canine vector-borne protozoal infections. It is important to note that the peptide-drug associations reported in this study are based on in silico predictions using the STITCH database and have not been experimentally validated. These findings should be interpreted with caution and viewed as preliminary hypotheses to guide future research. Functional assays and targeted studies will be required to confirm these interactions.

To advance toward clinical translation, future studies should focus on validation steps such as targeted LC-MS/MS or ELISA development for quantifying specific biomarker peptides. Additionally, comparison with existing canine plasma proteome reference datasets may provide further insights into peptide specificity and improve diagnostic accuracy.

Limitations and perspectives

Despite the promising findings, this study is limited by a relatively small sample size and the lack of cross-validation with other vector-borne diseases. Peptide expression profiles may vary by breed, disease stage, or co-infection status. Future research should aim to validate these biomarkers in larger, more diverse canine populations and assess their specificity compared to other parasitic infections. These results lay the foundation for developing rapid, peptide-based diagnostic tools that could improve early detection and disease monitoring in veterinary practice.

Conclusion

This study presents the first successful application of serum peptidomic profiling using MALDI-TOF MS and LC-MS/MS to identify potential biomarker peptides associated with Hepatozoon canis infection in dogs. The findings demonstrate the utility of peptide mass fingerprints in distinguishing infected from healthy individuals, offering new diagnostic insights. Notably, the identified peptide candidates and their predicted interactions with commonly used antiparasitic drugs support the potential for diagnostic and therapeutic development. Further large-scale validation is needed to confirm these biomarkers and translate them into clinically applicable tools in veterinary parasitology.