Open Veterinary Journal, (2026), Vol. 16(4): 2212-2231

Research Article

10.5455/OVJ.2026.v16.i4.23

Comparative gut microbial enzyme functions in human amoebiasis: Implications for host–microbe interactions and veterinary parasitic models

Dalia A. Abuljadayel^*

Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia

*Corresponding Author: Dalia A. Abuljadayel. Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia. Email: Dabuljadayel [at] kau.edu.sa

Submitted: 27/10/2025 Revised: 27/02/2026 Accepted: 16/03/2026 Published: 30/04/2026

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ABSTRACT

Background: The intestinal microbiome is a critical component of host defense and metabolic regulation in both humans and animals. Parasitic infections such as amebiasis disrupt microbial enzyme activities, potentially influencing host physiology.

Aim: To investigate functional differences in gut microbial enzymes between humans infected with Entameba histolytica and healthy controls and to provide insights relevant to comparative parasitic pathobiology.

Methods: Stool samples collected from patients diagnosed with amebiasis, as well as from healthy control individuals, were analyzed using 16S rRNA gene sequencing. KEGG-based annotation tools were used to generate functional enzyme predictions, and differential pathway enrichment was assessed across hierarchical metabolic levels.

Results: The results showed that healthy controls displayed greater representation of metabolic, genetic, and environmental information pathways. In contrast, amebiasis patients showed enrichment in membrane transport and energy metabolism. Glycolytic and oxidative stress-related enzymes, including 6-phosphofructokinase, phosphoglycerate mutase, and peroxiredoxin, were significantly more abundant in the infected group. Conversely, enzymes linked to amino acid biosynthesis and DNA repair—such as phosphoglycolate phosphatase and NADH: ubiquinone reductase—were markedly reduced, indicating a functional shift toward energy mobilization and stress adaptation.

Conclusion: In conclusion, amebiasis induces the reorganization of gut microbial enzyme functions, enhancing glycolytic and transport activities while suppressing biosynthetic and repair processes. These findings may also provide valuable comparative insights for veterinary medicine, as similar host–parasite–microbiome interactions occur in several protozoal infections affecting domestic and wild animals. Understanding microbial enzyme responses during protozoal infection could therefore contribute to improved interpretation of microbiome-associated pathophysiology in veterinary parasitology.

Keywords: Amebiasis, Enzyme function, Gut microbiota, KEGG pathway, Microbial metabolism.

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Introduction

Amebiasis is a parasitic infection caused by the protozoan Entameba histolytica (EH), with amebic colitis and amebic liver abscess being the most common and severe clinical manifestations. Advances in molecular diagnostics have enabled accurate discrimination between pathogenic and non-pathogenic Entameba species, resolving long-standing diagnostic ambiguities (Blessmann et al., 2002; Gupta et al., 2022). Although early estimates suggested that up to 500 million people worldwide were infected with the EH complex, contemporary data indicate that amebiasis continues to pose a major public health burden, with tens of millions of infections annually and an estimated 40,000–110,000 deaths per year due to invasive disease. The burden is disproportionately higher among vulnerable populations, particularly children, individuals living in low- and middle-income countries with inadequate sanitation, malnourished populations, and travelers or migrants from endemic regions, underscoring the influence of socioeconomic and environmental factors on disease transmission and outcomes (Servian et al., 2022; Morán et al., 2023).

The genus Entameba comprises several species inhabiting the human gastrointestinal tract, including EH, E. dispar, E. hartmanni, E. coli, and E. polecki and E. moshkovskii. Although EH, E. dispar, and E. moshkovskii cysts are morphologically indistinguishable, they are genetically and biochemically distinct, with only EH being invasive and pathogenic (Diamond and Clark, 1993; Haque et al., 2003; Fotedar et al., 2007). The parasite has a simple life cycle comprising environmentally resistant cysts and metabolically active trophozoites. After ingestion of cysts through contaminated food or water, excystation occurs in the intestine, releasing trophozoites that multiply by binary fission. These trophozoites can invade intestinal epithelial tissue, disrupt the mucosal barrier, and disseminate to extraintestinal organs such as the liver, lungs, and brain via the bloodstream (Nozaki and Bhattacharya, 2014; Baig et al., 2024).

The human large intestine harbors a dense and diverse gut microbiome composed of nearly 1,000 bacterial species, which collectively play a fundamental role in host immunity, nutrient metabolism, and susceptibility to infectious diseases. This microbial ecosystem is influenced by host genetics, diet, age, health status, stress, and exposure to antimicrobials (Carrero et al., 2020). Increasing evidence demonstrates that the gut microbiota are not merely a passive bystander but actively modulates EH colonization, virulence, and disease severity. Interactions between the parasite and specific enteric bacteria can enhance amebic pathogenicity by triggering virulence-associated traits, such as cytotoxicity, tissue invasion, and immune evasion, thereby promoting mixed infections (Galván-Moroyoqui et al., 2011; Guillén, 2023). Conversely, certain commensal bacteria exert protective effects by regulating host immune responses, redox balance, and parasite metabolism.

Microbial enzyme functions represent a critical interface between the gut microbiome and host–parasite interactions. Parasitic infections can induce substantial shifts in microbial enzyme profiles, reflecting altered metabolic demands, oxidative stress responses, and nutrient availability within the gut environment. Oxidative stress generated during infection can reshape microbial metabolic activity, whereas enteric bacteria may regulate homeostatic mechanisms that indirectly support the survival of EH. Transcriptomic and metagenomic studies have shown that gut bacteria can modulate key metabolic and regulatory pathways essential for amebic persistence (Varet et al., 2018; Kurniawan et al., 2025). The 16S rRNA gene remains a cornerstone molecular marker for profiling microbial communities because it combines conserved regions necessary for universal amplification with hypervariable regions that enable taxonomic resolution at the genus and species levels.

Experimental evidence further highlights the functional importance of microbiome–parasite interactions. Colonization with segmented filamentous bacteria (SFB), for example, protects against EH infection in murine models by enhancing neutrophil recruitment, dendritic cell activation, and IL-17A-mediated immune responses in the gut. Bone marrow-derived dendritic cells from SFB-colonized hosts produce elevated IL-23 levels upon trophozoite stimulation, and their adoptive transfer is sufficient to confer protection, emphasizing the role of microbiome-driven immune modulation beyond the intestinal compartment (Burgess et al., 2014; Uddin et al., 2021). From a metabolic perspective, EH exhibits a highly reduced and atypical metabolism. The parasite lacks mitochondria, hydrogenosomes, the tricarboxylic acid (TCA) cycle, and oxidative phosphorylation machinery, and instead relies on glycolysis and fermentative pathways for Adenosine Triphosphate (ATP) production (Anderson and Loftus, 2005; Jeelani and Nozaki, 2014). Pyruvate is converted to acetyl-CoA via pyruvate:ferredoxin oxidoreductase, with downstream conversion to acetate or ethanol to support ATP synthesis and NAD⁺ regeneration (Moffett et al., 2020). Genomic analyses reveal extensive gene loss in pathways such as purine and pyrimidine biosynthesis, folate metabolism, and ribonucleotide reduction, alongside lateral gene transfer from bacteria, collectively shaping a metabolism that is strongly influenced by the surrounding microbial community (Santos and Nozaki, 2022).

Despite significant progress in elucidating the biology of EH and its pathogenic mechanisms, considerable knowledge deficits persist concerning the impact of gut microbiome-derived enzyme functions on parasite metabolism and disease advancement in vivo. Most current research emphasizes taxonomic composition or descriptive correlations, with minimal functional predictions connecting microbial enzymes to metabolic alterations during infection. The effects of amebiasis on microbial energy metabolism, redox regulation, and biosynthetic capacity, as well as the distinctions between these alterations and healthy states, have not been adequately characterized.

Protozoal parasitic infections similar to EH are widely reported in animals and represent an important concern in veterinary medicine. The interaction between intestinal parasites and the gut microbiome has been increasingly recognized as a key factor influencing disease outcome, host immunity, and metabolic adaptation in both human and animal hosts. Studies in veterinary parasitology have shown that alterations in microbial composition and enzyme activities can influence the pathogenicity of several enteric protozoa infecting livestock and companion animals. Therefore, investigating microbial enzyme functions during amebiasis may offer comparative insights that extend beyond human medicine and contribute to a broader understanding of host–microbiome–parasite interactions relevant to veterinary infectious diseases.

Consequently, it is imperative to compare microbial enzyme functions between amebiasis patients and healthy individuals to clarify the functional reprogramming of the gut microbiome during infection. These comparisons elucidate metabolic adaptations, stress responses, and host–parasite–microbiome interactions that may influence disease severity and persistence. In this context, the current study seeks to predict and delineate microbial functional profiles in amebiasis by systematically examining enzyme-associated pathways related to EH metabolism, thereby filling a significant void in our understanding of functional host–microbiome–parasite interactions.

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Materials and Methods

Sample collection and purification of DNA

A total of 9 patients aged 18–60 years with a laboratory-confirmed diagnosis of amebiasis were enrolled in the study to minimize age-related variability in gut microbiome composition. The diagnosis of amebiasis was determined through an initial microscopic analysis of stool samples for cysts and trophozoites, followed by molecular validation via polymerase chain reaction (PCR) to differentiate pathogenic EH from morphologically analogous nonpathogenic species. The final analysis included only patients with EH infection confirmed by PCR. All enrolled patients exhibited intestinal amebiasis of mild to moderate clinical severity, marked by diarrhea and abdominal discomfort, without indications of extraintestinal involvement, such as amebic liver abscess. To minimize heterogeneity associated with disease severity, patients exhibiting severe disease manifestations or extra-intestinal amebiasis were excluded. This approach was chosen because the severity of the disease may change the gut microbiota’s makeup through inflammation, tissue invasion, and changes in the host’s immune response, making microbiome-based functional predictions less accurate.

Eligible participants had no prior use of antibiotics, antiparasitics, probiotics, or prebiotics for a minimum of 4 weeks before sample collection and had no chronic gastrointestinal or systemic diseases recognized to affect the composition of the gut microbiota. Patients who had recently received antimicrobial treatment, co-infection with other intestinal parasites or enteric bacterial pathogens, chronic inflammatory bowel disease, metabolic or immunosuppressive conditions, recent hospitalization, pregnancy, or inability to provide informed consent were excluded. We used a Microbiome Collection Kit (ISM-T-1200-R; Mawi DNA Technology, USA) to collect fecal samples from hospitalized patients. The samples were then stored at −20°C until DNA extraction.

Purification of DNA from fecal samples

A total of 18 fecal samples—9 from patients with amebiasis (P) and 9 from healthy controls (C)—were subjected to DNA extraction. Total genomic DNA was extracted exclusively using the QIAamp Fast DNA Stool Mini Kit (QIAGEN, USA; Cat. No. 51604) according to the manufacturer’s instructions. Approximately 200 mg of stool was processed per sample, and InhibitEX Buffer (QIAGEN) was used to remove PCR inhibitors commonly present in fecal material. The concentration (ng/µl) and purity of the extracted DNA were measured using a NanoDrop 2000c spectrophotometer (Thermo Scientific, USA). DNA samples with concentrations ≥20 ng/µl, an A260/280 ratio between 1.8 and 2.0, and an A260/230 ratio ≥2.0 were considered of sufficient quality and selected for downstream library preparation.

For bacterial community profiling, PCR amplification of the V3–V4 hypervariable region of the bacterial 16S rRNA gene was performed using validated universal primers commonly used for V3–V4 amplicon sequencing: forward primer 341F (5′-CCTACGGGNGGCWGCAG-3′) and reverse primer 785R (5′-GACTACHVGGGTATCTAATCC-3′). Primer sequences are written in the 5′ to 3′ orientation and were selected based on previous studies.

PCR amplification was performed in a 25-µl reaction volume containing 12.5 µl of 2 × PCR Master Mix (e.g., KAPA HiFi HotStart ReadyMix, Roche), 0.2 µM of each primer, and approximately 20 ng of template DNA. Amplifications were performed on a thermal cycler (e.g., Applied Biosystems Veriti™, USA) under the following conditions: initial denaturation at 95°C for 3 minutes; 25 cycles of denaturation at 95°C for 30 seconds, annealing at 55°C for 30 seconds, and extension at 72°C for 30 seconds; followed by a final extension at 72°C for 5 minutes. The PCR products were verified by agarose gel electrophoresis (1.5%), purified using AMPure XP magnetic beads (Beckman Colter), and indexed according to the Illumina 16S Metagenomic Sequencing Library Preparation protocol. Paired-end sequencing (2 × 300 bp) was performed using an Illumina MiSeq platform (Illumina, USA). All laboratory procedures were conducted under identical conditions to minimize technical variation among samples.

Data analysis

To determine the function of the microbial community in patients with amebiasis, we started with raw data, which was cleaned to provide clean, high-quality data. Clean readings that can overlap are then combined into tags and further grouped into operational taxonomic units (OTUs). The Ribosomal Database Project database is used to assign taxonomic classes to OTU representative sequences. The following procedure was used to filter raw sequencing data to obtain clean, high-quality reads: reads were truncated if their average Phred quality score within a 25 bp sliding window was below 20. Reads contaminated with adapter sequences or those retaining less than 75% of their original length after truncation were removed (default parameter: 15 bases spanned by reads and adapter with a maximum of 3 base mismatches allowed). Additionally, reads that have an unclear basis (N base) are eliminated. Internal programs allocated clean reads to appropriate samples using alignments (0 base mismatch) toward barcode sequences to guarantee the removal of barcode sequences from pooling libraries.

Tags connection: FLASH (Fast Length Adjustment of Short reads, v1.2.11) will provide a consensus sequence if paired-end reads overlap. A taxon unit (seven taxonomy levels) was analyzed using OTU clustering. Then, using USEARCH (v7.0.1090), tags were clustered into OTU; the following details are provided:

1) UPARSE clusters tags into OTUs with a 97% threshold, allowing for the extraction of unique OTU representative sequences; 2) UCHIME (v4.2.40) filters chimeras. Chimeras in the OTU were screened and filtered for 16S rDNA and Internal Transcribed Spacer (ITS) sequences by mapping to the gold database (v20110519) and the UNITE database (v20140703), respectively, while de novo chimera screening was used for 18S rDNA sequences.

To determine the types of microbes present, we grouped high-quality reads into OTUs and then analyzed the sequencing data. Using the biodiversity and community analysis software (v3.2.1), OTU clustering was performed at a sequence similarity threshold of 97% after quality filtering. Before performing any further analyses, chimera sequences were identified and removed to reduce artifacts. For 16S rRNA gene sequences, chimera screening was performed through reference-based mapping to the Gold database (v20110519), whereas ITS sequences were filtered using the UNITE database (v20140703). De novo chimera detection was utilized for 18S rRNA gene sequences. Only non-chimeric OTUs were retained for later analyses of diversity, community structure, and functional prediction.

Statistical analysis and functional prediction of the results

PICRUSt2 (v2.3.0-b) in R software (v3.4.1) was used to predict the functional potential of the gut microbiome from 16S rRNA gene sequencing data. This method uses HSP to put amplicon sequence variants into a reference phylogenetic tree and guess how many gene families there are. We used the KEGG Orthology (KO), Clusters of Orthologous Groups (COG), and MetaCyc metabolic pathway databases to add the predicted functions.

Functional prediction in the KEGG database

Using KO identifiers to guess pathway abundances at three hierarchical levels (levels I–III), we predicted KEGG functions. These levels represent general functional groups, functional subgroups, and specific metabolic pathways. We used relative abundance tables for each KEGG level to compare amebiasis patients to healthy controls.

Classification of the COG functions

Using PICRUSt2, we performed functional prediction based on COG. We then summarized the results at COG level 1 (broad functional categories) and COG level 2 (specific functional classes) to show how the microbial functional capacity of the groups differed.

Analysis of the MetaCyc pathway

MetaCyc pathway profiles were used to determine changes in primary and secondary metabolic pathways. These pathways involved energy metabolism, amino acid biosynthesis, and carbohydrate utilization. Three levels of hierarchy were used to analyze the MetaCyc pathways. Level 3 provided detailed descriptions of the pathways.

Differential functional analysis

The Wilcoxon rank-sum test was used to find statistically significant differences in predicted microbial functions between groups (amebiasis vs. control). Bar plots and heatmaps were used to show the results, focusing on the pathways and enzymes that were most important to infection-related metabolic changes.

Multivariate and correlation analyses

To investigate the relationships between microbial functional profiles and sample grouping, redundancy analysis (RDA) was conducted using predicted functional abundance data. RDA was chosen after detrended correspondence analysis, which demonstrated gradient lengths <3.0, thereby endorsing a linear model.

Spearman correlation analysis was used to examine the relationships between dominant microbial taxa (with a relative abundance of >0.5%) and important functional pathways. We used R software to create correlation heatmaps that only show statistically significant correlations (|r| > 0.2).

Visualizing networks and applying machine learning

Cytoscape software was used to create interaction networks that show how dominant microbial taxa and significantly changed functional pathways are connected. This shows possible microbe-function relationships that may be linked to amebiasis.

We used RF classification analysis to see how well predicted microbial functions could tell the difference between different groups. The samples were randomly divided into 70% training and 30% testing datasets. To ensure that the model was strong, we repeated 10-fold cross-validation 10 times. Receiver operating characteristic curves and area under the curve values were used to measure how well the model worked.

Ethical approval

The Institutional Review Board (IRB) approved the study under ethical approval number 00785 (IRB registration number with KACST: H-02-J-002), May 15, 2025, Jeddah, Saudi Arabia.

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Results

Sequencing of output and quality control

All fecal samples from patients with amebiasis and healthy controls exhibited positive PCR amplification of the bacterial 16S rRNA gene, thereby confirming the presence of microbial DNA in each sample. High-throughput sequencing produced approximately 1,260,000 raw paired-end reads from the 18 samples. After filtering for quality, which included cutting off low-quality bases, removing adapters, and removing chimeras, approximately 1,080,000 high-quality clean reads were retained, with an average of approximately 60,000 reads per sample. No samples were omitted because of inadequate read depth, demonstrating consistent amplification and sequencing efficiency across groups.

After trimming, the sequences matched the expected V3–V4 region of the 16S rRNA gene. The average sequence length across all samples was about ~460 bp, and there were no noticeable differences in the distribution of read lengths between patients and controls.

Taxonomic assignment and analysis of similarity

Using BLAST-based similarity searches, we compared representative OTU sequences to curated reference databases, such as SILVA/NCBI. Most of the sequences were at least 97% of known bacterial taxa, which made it possible to reliably classify them at the genus level and, in some cases, at the species level. Most of the dominant matches were linked to common groups of bacteria, such as Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria, that live in the human gut.

The resulting 16S rRNA sequences exhibited distinct similarity profiles among patients, indicating inter-individual variability in the composition of the gut microbiota. Nevertheless, patients with amebiasis exhibited broadly analogous functional and taxonomic patterns that were distinguishable from those of healthy controls, infection-related microbial reorganization rather than colonization by a singular, uniform microbial species.

Functional profiling based on the KEGG pathway

At the KEGG level I, enriched pathways associated with the predicted gene content between the two groups indicated that environmental information processing, human diseases, and metabolism represented the highest relative abundances. The healthy control group had more metabolic and genetic information processing than the other groups (Table 1, Fig. 1).

Fig. 1. (A, B): Abundance and relative abundance at level 1 (category) refer to the most abundant enzymes that decreased in enrichment in patients with amebiasis.

Table 1. Level (category) the differences between the patient and control groups.

Ko level 1 between the patients and control groups.

At KEGG level II (functional subcategories), the gut microbiome of amebiasis patients showed a greater abundance of enriched functionally predicted enzymes than healthy controls. The most common metabolic processes were carbohydrate metabolism, amino acid metabolism, cofactor and vitamin metabolism, and other metabolic processes. On the other hand, the control group had fewer predicted enzyme subcategories related to energy metabolism, carbohydrate metabolism, cofactor and vitamin metabolism, and membrane transport (Table 2, Fig. 2). Carbohydrate metabolism and membrane transport exhibited diminished relative abundance in controls (13.9 and 1.4, respectively) compared with patients suffering from amebiasis (16.7 and 2.4, respectively).

Fig. 2. (A, B): Abundance and relative abundance at level 2 (subcategory) refer to the most abundant enzymes that decreased in enrichment in patients with Amebiasis.

Table 2. Ko level (subcategory) between patients and controls.

Ko level 2 (subcategory) between patients and controls.

At KEGG level III (pathway level), the control group had fewer enzymes in most pathways than the patient group. The most important pathways were glycan degradation, branched-chain amino acid biosynthesis (valine, leucine, and isoleucine), glutamate and aspartate metabolism, and peptidoglycan biosynthesis (Table 3, Fig. 3).

Fig. 3. (A and B): Abundance and relative abundance at level 3 pathways refer to the most abundant enzymes that decreased in enrichment in patients with Amebiasis.

Table 3. Enzyme pathways at the Ko level between patients and controls.

At the enzyme level (KEGG level IV), approximately 20 enzymes were much more common in the healthy control group than in people with amebiasis. These enzymes included phosphoglycolate phosphatase (PGP; EC 3.1.3.18), NADH: ubiquinone reductase (EC 1.6.5.3), α-L-fucosidase (EC 3.2.1.51), β-glucosidase (EC 3.2.1.21), tryptophan synthase (EC 4.2.1.20), ATP-dependent DNA helicase UvrD/PcrA (EC 3.6.4.12), DNA topoisomerase (EC 5.99.1.3), histidine kinases (EC 2.7.13.3), and signal peptidase I (EC 3.4.21.89). Patients had >50% fewer enzymes than healthy controls (Fig. 4).

Fig. 4. (A and B): Abundance and relative abundance of the most abundant enzymes that decreased in enrichment in patients with Amebiasis. Column with gray color refers to enzymes with a decreased abundance of ›50% in patients compared with the healthy control.

On the other hand, acetyl-CoA carboxylase (EC 6.4.1.2), archaeal-type DNA polymerase (EC 2.7.7.7), phosphoglycerate mutase (EC 5.4.2.12), and phenylalanine- transfer RNA (tRNA) ligase (EC 6.1.1.20) were all enzymes that did not show any significant differences between groups. Some enzymes, such as peroxiredoxin (EC 1.11.1.15), were found in higher amounts in people with amebiasis. The body responds more strongly to oxidative stress when infected.

The carbohydrate metabolism and membrane transport subcategories included many enzymes from different pathways, indicating their importance for infection. In carbohydrate metabolism, the glycolysis/gluconeogenesis pathways comprise essential enzymes, including aldose-1-epimerase (EC 5.1.3.3), 6-phosphofructokinase (EC 2.7.1.11), and phosphoglycerate mutase (EC 5.4.2.12) (Fig. S1). These enzymes are also connected to the pentose phosphate and citrate cycle pathways, which help produce pyruvate and other fermentation products.

Phosphoglycolate phosphatase (PGP; EC 3.1.3.18) is involved in glyoxylate and dicarboxylate metabolism. It connects glycolytic intermediates to the metabolism of glycine, serine, and threonine (Fig. S2). Oxaloacetate decarboxylase, an important enzyme in pyruvate metabolism, also helps oxaloacetate turnover during metabolic adaptation.

In membrane transport, the ABC-type ferric hydroxamate transporter and iron-chelate–transporting ATPase (EC 3.6.3.34) were both enriched. These two proteins are part of the ABC transporter pathway, indicating that the way amebas get iron has changed (Fig. 4A and B; Fig. S3).

Five pathways and six key enzymes were found to be enriched in amino acid metabolism. These include carbamoyl-phosphate synthase (EC 6.3.5.5) and glutamate-ammonia ligase (EC 6.3.1.2) in arginine biosynthesis, aspartate kinase (EC 2.7.2.4) and tryptophan synthase (EC 4.2.1.20) in serine, glycine, and threonine metabolism, and cystathionine β-lyase (EC 4.4.1.8) and acetolactate synthase (EC 2.2.1.6) in methionine/cysteine metabolism and branched-chain amino acid biosynthesis, respectively. Only three of these enzymes showed a decrease of more than 50% in patients compared with controls (Fig. 4A andB).

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Discussion

This study showed that illness was associated with noticeable changes in predicted functional enzyme profiles between patients with amebiasis and healthy controls, although the specific microbiome alterations responsible for these changes were not determined. The results also highlighted that at different levels of KEGG pathways, among the top 40 enriched rate-III KEGG pathways in the two groups. For example, the “Other glycan degradation” pathway, includes α-L-fucosidases, which belong to the GH29 (glycoside hydrolase family 29). AFUs play significant roles in various biological processes and serve as biomarkers for the detection of HCC (Yu et al., 2019). Furthermore, AFU has been shown to possess prognostic value for long-term survival in healthy individuals with early-stage ESCC (ESCC) (Yu et al., 2019).

From a veterinary perspective, these observations may have broader implications. Several protozoal parasites infect animals and interact with the intestinal microbiota in ways that resemble host–microbe–parasite dynamics observed in human amebiasis. Consequently, the functional microbial shifts detected in the present study may provide a comparative framework for future investigations into microbiome-mediated responses to parasitic infections in veterinary species.

In addition, AFUs are involved in key physiological functions, such as inflammation, growth regulation, receptor interactions, and antigenicity. Notably, their substrate specificity is highly dependent on the source organism, which may include bacteria, fungi, mollusks, plants, and mammals (Bojarová-Fialová and Křen, 2007; Rao, 2024). Its role is to provide evidence to explain its abundance within the healthy group. The valine, leucine, and isoleucine biosynthesis pathways involve acetolactate synthase, which catalyzes the condensation of pyruvate with either a second pyruvate molecule to form α-acetolactate or with α-ketobutyrate to form α-acetohydroxybutyrate. These reactions are key steps in the biosynthetic pathways leading to the production of valine and isoleucine. Two isoforms of Salmonella (ALS I and ALS II) play distinct roles. Inhibition of ALS II by sulfonylurea herbicides disrupts branched-chain amino acid and pantothenate synthesis by altering metabolic flux through the accumulation of α-ketobutyrate (Reeve, 2014; Székács, 2021).

2-Oxoglutarate (EC 1.2.7.3), also definite as α-ketoglutarate, is a central intermediate in the TCA cycle in the carbohydrate metabolism category. It plays a critical role in nitrogen assimilation and supports amino acid biosynthesis by contributing to succinyl-CoA production, which is also involved in the biosynthesis of porphyrin and heme via ALA synthase (Bonkovsky et al., 2013). The 2-oxoglutarate dehydrogenase complex links mitochondrial metabolism to gene expression, with implications for aging and tumor progression (Noor et al., 2010; Nemeria et al., 2021).

Site-specific DNA methyltransferases (DNMTs) play a crucial role in the carbohydrate metabolism subcategory and are functionally associated with the mismatch repair system. As members of the "writer" enzyme family, DNMTs mediate. DNA methylation is an important epigenetic change that controls gene expression without changing the fundamental DNA sequence. DNA methylation facilitates the recruitment of m5C-binding proteins, which act as transcriptional repressors (Chen et al., 2021). Additionally, methylation initiates histone deacetylation, leading to chromatin condensation and the establishment of stable, long-term transcriptional repression (Meehan et al., 1992; Dobosy and Selker, 2001).

The results indicate significant enrichment of enzymes in the peptidoglycan biosynthesis pathway, particularly serine-type D-Ala-D-Ala carboxypeptidase and undecaprenyl-diphosphate phosphatase, in the control group (EC 3.6.1.27). These enzymes are involved in glycan biosynthesis and are linked to lysostaphin activity, a potent bacteriolytic enzyme effective against Staphylococcus species, containing (Methicillin-Resistant Staphylococcus aureus), by targeting and disrupting peptidoglycan and biofilms (Haddad Kashani et al., 2018; Gonzalez-Delgado et al., 2019).

The results show that within the carbohydrate metabolism subcategory, the glycolysis/gluconeogenesis pathway includes key enzymes such as 6-phosphofructokinase, phosphoglycerate mutase (PGM), and aldose 1-epimerase. The first enzyme converts fructose-6-phosphate to fructose-2,6-biphosphate using one ATP molecule for dephosphorylation (Fernandes et al., 2020), whereas the second enzyme contributes to pentose phosphate (PPP). PPP is essential for carbon homeostasis, nucleotide and amino acid biosynthesis, anabolic reducing power, and combating oxidative stress (Fang and Xu, 2025). Glycolysis provides pyruvate and key intermediates, such as fructose-6-phosphate, glycerate-3-phosphate, and α-glucose for energy production and other metabolic processes. In EH, which lacks oxidative phosphorylation and Krebs cycle enzymes, glycolysis serves as the primary ATP source and supplies macromolecule synthesis precursors. (Pineda et al., 2015b). The third enzyme, EC 5.4.2.12, is a key enzyme in glycolysis that catalyzes the reversible conversion of 3-phosphoglycerate to 2-phosphoglycerate, playing a vital role in glucose metabolism across diverse organisms (Zheng et al., 2025). The 2,3-diphosphoglycerate-independent form of PGM (iPGM) is particularly important in Bacillus anthracis. Studies have highlighted the catalytic mechanism of iPGM, emphasizing the role of bivalent metal ions and the influence of intracellular pH changes on enzyme regulation during spore production and germination (Nukui et al., 2007).

Transketolase, a glycolaldehyde transferase (EC 2.2.1.1), exists inside the pentose phosphate pathway of the carbohydrate metabolism subcategory and metabolism category. Enabling the production of several vitamins, coenzymes, and precursors for nucleotide synthesis as well as the pentose phosphate pathway of carbohydrate transformation and glycolysis, which allows the cell to quickly adjust to its metabolic needs, is important (Kochetov and Solovjeva, 2014).

Beta-N-acetylhexosaminidase (EC 3.2.1.52) is an enzyme involved in the metabolism of amino and nucleotide sugars. In the pathway, it is clear to demonstrate its impacts as compounds of the cell wall of fungi, the initial line of protection toward host-induced antifungal activity is provided by the fungal cell wall components, an important organelle (Keffeler et al., 2021). Chitosan, one of the cell wall’s carbohydrate polymers, has a big impact on how the host and pathogen interact. Chitosan is a crucial component of virulence because avirulent strains lack it. C. gattii R265 is a significant fungal pathogen of concern due to its growing geographic range and capacity to infect people without obvious immunological dysfunction (Lam et al., 2019). In addition, cysteine desulfurase (EC 2.8.1.7) exists in the thiamine pathway under the vitamins and cofactors metabolism subcategory in the KEGG metabolism category. The metabolism of purine and vitamin B6 is the starting point for the generation of thiamine acetic acid and thiamine triphosphate, which are catalyzed via the L-cysteine substrate (Kanehisa et al., 2016). The microbial community may maintain cysteine desulfurase activity to support basic metabolic functions, even during infection-induced shifts in microbial composition (Braymer and Lill, 2017).

Membrane transport contains two enzymes under the ABC transporter pathway: the ABC-type ferric hydroxamate transporter (EC 3.6.3.34 it transfer to EC 7.2.2.17) and Iron-chelate-transporting ATPase (EC 3.6.3.34). These enzymes play a role during infection because pathogens, such as G+ bacteria, G bacteria, and archaea, require iron as an essential nutrient. Therefore, ABC systems, which transport iron or metal types, are found in many bacterial strains, such as Archaeoglobus fulgidus, Enterococcus faecalis, Bacillus subtilis, Escherichia coli, and Erysipelothrix rhusiopathiae, for the acquisition of iron. For example, iron- and fur-regulated sit ABCD operon genes of Salmonella enterica serova Typhimurium are expressed under iron-deficient conditions (Koster, 2005).

ABC transport systems of the iron or metal type are found in many bacterial types (Attwood, 2013). Furthermore, the F-type H+/Na+-transporting ATPase subunit alpha (EC 3.6.3.14) (inside oxidative phosphorylation) has a vital impact on the metabolism energy category under oxidative phosphorylation. Enzymes can hydrolyze ATP, which is produced by glycolysis, to be used for cell function. The antibacterial effect of N-acetylmuramoyl l-alanine amidase (EC 3.5.1.28) belongs to the following categories: organismal systems, immune system categories, and subcategories. Its signaling pathway (Toll and Imd signaling), which demonstrates its role in defense and wound response. The high abundance of this enzyme reflects its crucial role in wound repair, degradation, and immune defense. It functions by catalyzing the cleavage of the bond between L-amino acid residues and N-acetylmuramoyl in specific cell wall glycopeptides. In Entameba, this enzyme supports defense by degrading microbial elements and aiding tissue repair (Ankri, 2021). F-type ATP synthases, membrane-bound enzymes in EH, which lack mitochondria, utilize the proton motive force (pmf) to synthesize ATP or, conversely, hydrolyze ATP to generate pmf for essential cellular processes under anaerobic conditions (Mellroth and Steiner, 2006; Walker, 2013).

The DNA replication pathway, involving enzymes such as DNA helicase (EC 3.6.4.12), DNA polymerase, archaea type (EC 2.7.7.7), and ribonuclease H (EC 3.1.26.4), is essential for Entameba, as these enzymes utilize the energy from NTP hydrolysis to unwind duplex DNA into single strands. This function is critical for fundamental cellular processes in eukaryotic cells, such as growth, repair, and regeneration. Survival of protozoan parasites is heavily dependent on efficient DNA repair mechanisms, which continuously monitor and maintain genome integrity by correcting nucleotide damage caused by cytotoxic agents, host immune responses, or intracellular metabolic processes. Moreover, nuclear gene transcription in eukaryotes involves three DNA-directed RNA polymerases, Pol I, Pol II, and Pol III, each consisting of a core set of 12 subunits along with specific auxiliary components (Devaux et al., 2007; López-Camarillo et al., 2009. 23S rRNA pseudouridine functional enzyme (EC 5.4.99.23), involved in ribosome biogenesis in the eukaryotic pathway, helps in modifying other RNAs by enhancing their structural stability and functional efficiency. In mRNA and pre-mRNA, they guide splicing and shield transcripts from degradation, serving as a defense against viral infections (Khan et al., 2023).

Inside the aminoacyl-tRNA biosynthesis pathway, under the translation subcategory of KEGG, ribosome biogenesis by phenylalanine-tRNA ligase (EC 6.1.1.20) is a highly regulated cellular process for growth and cell development. The aaRS proofreading processes that guarantee proper attachment of a corresponding amino acid to a tRNA contribute to accurate translation of the genetic code. Changes in cytoplasmic amino acid availability during environmental stress, such as oxidative stress, modify the demands on aaRS proofreading (Steiner et al., 2019).

Signal peptidase I (EC 3.4.21.89) is an important enzyme in the protein export pathway, the functional importance of which lies in its indispensable role in cleaving signal peptides from preproteins during translocation across membranes. It is essential for bacterial viability and represents a potential antibacterial target (Tuteja, 2005).

The OmpR/PhoB family represents the largest class of response regulators in the bacterial two-component system pathway (TCS). These proteins are activated by phosphorylation from their partner histidine kinases (EC 2.7.13.3), triggering structural changes that enable dimerization and increased DNA-binding activity, thereby regulating gene expression (Barbieri et al., 2013; Nguyen et al., 2015). These groups with TCS contribute to adaptive responses within the MTS subcategory. Similar protective mechanisms are observed in EH. The parasite utilizes bacterial metabolites and penetrates biofilms to shield itself from reactive oxygen species, using the biofilm matrix as a defense layer (Barbieri et al., 2013; Ankri, 2021; Zanditenas et al., 2023).

The results highlight only one enzyme, DNA topoisomerase (ATP-hydrolyzing) (EC 5.99.1.3), which belongs to the platinum drug resistance pathway and is classified as a human disease. It plays a crucial role in solving DNA problems. The low abundance of this enzyme in amebiasis patients may relate to its role in resolving DNA supercoiling during replication, transcription, and repair. Its catalytic tyrosine mediates DNA cleavage and rejoining, a mechanism targeted by various cytotoxic and anticancer agents. (Chen et al., 2013). Moreover, EH lacks antioxidant enzymes, such as glutathione reductase, catalase, and γ-glutamyl transpeptidase (Ankri, 2021). Thus, proteins such as the 29-kDa peroxiredoxin (Sen et al., 2007) and iron-containing peroxide dismutase (Bruchhaus and Tannich, 1994) aid in oxidative stress (OS) resistance. It has been shown that EH types sustain exposure to OS better than avirulent strains due to the existence of peroxiredoxin (Davis et al., 2006; Iyer et al., 2014). As a result, there is a high abundance of peroxiredoxin, which is essential for OS resistance and contributes to the potential pathogenicity of EH (Rastew et al., 2012; Ankri, 2021).

Protein-Npi-phosphohistidine (EC 2.7.1.69) plays a role in the carbohydrate metabolism subcategory and the fructose and mannose metabolism pathway. It shares the path into glycolysis by its role in amino and nucleotide sugar metabolism. The role functions are facilitating PEP-dependent phosphoryl transfer to transport sugars across the cell membrane (Jeckelmann and Erni, 2019). In EH, fructose production through glycolysis is crucial, as its mitosomes lack oxidative phosphorylation and the TCA cycle. Therefore, energy generation mainly relies on cytosolic substrate-level fermentation and phosphorylation (Folch et al., 2021).

PGP enzyme under the dicarboxylate and Glyoxylate metabolism pathway and Carbohydrate metabolism subcategories (a prototypical metabolite repair enzyme in glycolysis, contributes to the generation of glycolate enzymes in glycolysis to end with glycine-serine and threonine metabolism, which is in agreement with another study that revealed that the functional and structural features of this enzyme PGP from E. coli are involved in the breakdown of intracellular 2-phosphoglycolate produced during DNA repair of 3'-phosphoglycolate ends (Pellicer et al., 2003), whereas alpha-glucosidase (EC 3.2.1.20), functioning within the metabolism pathway of galactose, contributes to the conversion ending in D-fructose. In EH, trophozoite adhesion to colonic mucins and host cells is mediated by a galactose-binding lectin, which is crucial for epithelial cell lysis; this binding is largely inhibited by β-D-galactose, though additional molecules may be involved (Zhai et al., 2022).

Alpha-glucosidase, a GH31 family enzyme that is widespread in the human gut microbiome, aids in carbohydrate metabolism by breaking down dietary polysaccharides. The structure of R. obeum closely resembles that of human maltase-glucoamylase, with a conserved catalytic domain (Tan et al., 2010). The enzyme prefers α (1-6) over α (1-4) linkages, and a single mutation can alter this preference, indicating microbial adaptation to diverse polysaccharide energy sources (Tan et al., 2010). In a similar subcategory, oxaloacetate decarboxylase (EC 4.1.1.3) plays a role in pyruvate metabolism, which was very abundant in the control. Shaulov et al. (2018) highlighted the role of EcMDH (E. coli malate dehydrogenase) and its product, one of the main components of E. coli-mediated oxidative stress resistance in EH is oxaloacetate, which also aids in the parasite’s survival in the large intestine. Additionally, we have shown that oxaloacetate protects Caenorhabditis elegans from oxidative stress (Shaulov et al., 2018).

Peroxiredoxin (PRDX1) is another enzyme present in the KEEG functional enzymes. Under pathway Peroxisome catabolism, subcategory transport and catabolism, category of cellular processes (Wanders et al., 2023), this enzyme shares a role in the hydrogen peroxide metabolism (PBI type), and it plays a role in the antioxidant system (Sadowska-Bartosz and Bartosz, 2023); therefore, its abundance is high within the patients group. Furthermore, peroxisomal proteins play an important role in the antioxidant system, specifically in the metabolism of epoxide and glutathione. Furthermore, another enzyme, such as β-Glucosidases (EC 3.2.1.21), which belongs to the metabolism category, the other amino acids metabolism subcategory, under cyanoamino acid metabolism pathway (Sengupta et al., 2023). There are many substrates for β-glucosidases in nature, including bacteria, eukaryotes, and archaea. It hydrolyzes β-1,4 glycosidic bonds in glucosides and related compounds to release glucose. These enzymes are widely distributed among archaea, eukaryotes, and bacteria and are predominantly classified within the GH1 and GH3 glycoside hydrolase families. They are integral to both primary and secondary metabolic pathways, contributing to plant cell wall degradation, lignification, and diverse microbial interactions. Their enzymatic activity is modulated by product concentration, and they are involved in phytohormone activation, defense responses, and characteristic flavor development in foods such as tea and wine (Sengupta et al., 2023).

Bacterial 3-oxoacyl-ACP reductase (OAR) (EC 1.1.1.100) and acetyl-CoA carboxylase (ACC) (EC 6.4.1.2) play a role in fatty acid synthesis. The former catalyzes the 3-oxoacyl-ACP minimizing step in the fatty acid synthesis pathway, which it also participates in the fatty acid and polyunsaturated fatty acid biosynthesis (Guo et al., 2022). At least 12 genes in the Pseudomonas aeruginosa genome are annotated as OAR-encoding genes (Guo et al., 2019). ACC catalyzes the formation of malonyl-CoA and is a key regulator of fatty acid biosynthesis. ACC is considered a potential therapeutic target for metabolic disorders like obesity due to its central impact on lipid metabolism (Lee et al., 2008).

Analysis of amino acid metabolism showed that there were more KEGG pathway–related enzymes, with about six enzymes found. Three of these showed a drop of more than 50% in patients compared to healthy controls: aspartate kinase (EC 2.7.2.4), cystathionine β-lyase (EC 4.4.1.8), and acetolactate synthase (EC 2.2.1.6). Aspartate kinase (EC 2.7.2.4) catalyzes the biosynthesis of essential amino acids, such as lysine, threonine, methionine, and isoleucine, by converting L-aspartate to L-aspartyl-phosphate, thereby supporting bacterial growth and metabolic activity, which may explain its altered abundance in the patient group (Suzuki, 2013). Cystathionine β-lyase (EC 4.4.1.8), an important enzyme in the metabolism of cysteine and methionine, is also involved in the forward transsulfuration pathway (methionine → homocysteine → cystathionine → cysteine), which is necessary for microbe survival and pathogenicity. This enzyme aids in the biosynthesis of sulfur amino acids in bacterial and protozoan pathogens, thereby enhancing virulence, oxidative stress resistance, and host colonization (Nair et al., 2025). The other three enzymes were more common in healthy controls than in patients: carbamoyl-phosphate synthase (glutamine-hydrolyzing) (EC 6.3.5.5), glutamate–ammonia ligase (EC 6.3.1.2), and tryptophan synthase (EC 4.2.1.20). Two of these enzymes are part of the arginine pathway. Carbamoyl-phosphate synthase (EC 6.3.5.5) facilitates the ATP-dependent synthesis of carbamoyl phosphate from glutamine and bicarbonate, serving as a rate-limiting step in de novo pyrimidine nucleotide biosynthesis. Aoki and Weber (1981) documented a 5.7- to 9.5-fold augmentation in CPS II activity within rapidly proliferating hepatoma tumors, associating enzyme upregulation with increased cellular proliferation and metabolic demand. Glutamate synthase (NADPH) (EC 1.4.1.13) is also involved in the breakdown of alanine, aspartate, and glutamate. It connects the pathways for breaking down carbon and nitrogen through the GS–GOGAT cycle. This enzyme is involved in both the production and breakdown of glutamate, and more microbiomes were found in the control microbiomes. In B. subtilis, the disruption of glutamate dehydrogenase hinders growth, highlighting the essential function of glutamate homeostasis in preserving cellular viability (Gunka and Commichau, 2012).

Ribonucleoside-diphosphate reductase (rNDP) (EC 1.17.4.1) is a nucleotide metabolism subcategory in the purine metabolism pathway. The enzyme rNDP has a critical impact in regulating the total level of DNA synthesis by maintaining balanced dNTP pools required for DNA replication so that DNA to cell mass is preserved at a constant ratio in cell division and DNA repair (Chandel, 2021).

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Conclusion

The intestinal microbiome is crucial for host metabolism and immune defense; however, the impact of amebiasis on microbial functional capacity is poorly understood. To fill this gap, the current study investigated enzyme activities from microbiomes that are linked to amebiasis. Our findings indicate a distinct functional reprogramming of the gut microbiota during infection, marked by the upregulation of membrane transport, glycolysis, and oxidative stress response pathways, as evidenced by the increased abundance of enzymes such as 6-phosphofructokinase, phosphoglycerate mutase, and peroxiredoxin. Conversely, healthy individuals demonstrated a heightened prevalence of metabolic, genetic, and environmental information-processing pathways, including enzymes associated with amino acid biosynthesis and DNA repair, which were significantly diminished in infected individuals. Collectively, these findings demonstrate that amebiasis induces a metabolic shift in the gut microbiome, favoring energy mobilization and stress adaptation while compromising biosynthetic and repair functions, offering novel insights into host–microbiome interactions during parasitic infection.

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Acknowledgments

The author would like to thank the Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Saudi Arabia, for their support.

Conflict of interest

The authors declare no conflict of interest.

Funding

This study received no funding.

Authors' contributions

D.A.A.: Conceptualization, investigation, data curation, formal analysis, original draft, validation, and review and editing.

Data availability

All data supporting the findings of this study are available within the manuscript; however, other Supplementary Figures can be provided upon request from the Corresponding Author.

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Supplementary Materials

Fig. S1. Enzymes in the pathway “Glycolysis / Gluconeogenesis” in healthy individuals compared with patients with amebiasis. EC 2.7.1.11=6-phosphofructokinase, EC 5.1.3.3=aldose 1-epimerase, EC 5.4.2.12=phosphoglycerate mutase (2,3-diphosphoglycerate-independent).

Fig. S2. Enriched enzymes in the “glyoxylate and dicarboxylate metabolism” pathway that contribute to a prototypical metabolite repair enzyme in glycolysis in healthy individuals compared with patients with amebiasis. EC 3.1.3.18=phosphoglycolate phosphatase.

Fig. S3. Enriched enzymes in the pathway “ABC transporters” that play a functional role in healthy individuals compared with patients with amebiasis. EC 3.6.3.34=iron-chelate-transporting ATPase; EC 3.6.3.34 (Fhuc)=ABC-type ferric hydroxamate transporter.