Gut microbial imbalances caused by unrestricted antibiotic use and exposure to chemical carcinogens contribute to liver and kidney toxicity: insights from in silico and in vivo studies

Gut microbial imbalances caused by unrestricted antibiotic use and exposure to chemical carcinogens contribute to liver and kidney toxicity: insights from in silico and in vivo studies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Gut microbial imbalances caused by unrestricted antibiotic use and exposure to chemical carcinogens contribute to liver and kidney toxicity: insights from in silico and in vivo studies Solomon Owumi, Dooshima, A. Bagu, Joseph Chimezie, Jesutosin O. Babalola, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9094434/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The gut microbiota is a complex community of microorganisms that play a vital role in human health; however, antibiotic administration can disturb this balance. Such disturbances have been linked to an increased risk of various diseases, including cancer. Notably, contamination of food with Aflatoxin B 1 (AFB 1 ) and Diethyl nitrosamine (DEN) has been shown to significantly raise the risk of liver cancer, as both agents are potent hepatocarcinogens associated with high incidences of hepatocellular carcinoma. This study examines the impact of widespread access to ampicillin (AMP) and ciprofloxacin (CPX)—two commonly used antibiotics in Nigeria—on the composition of the gut microbiota, dietary exposure to AFB 1 and DEN, and subsequent liver and kidney toxicity in rats. Using network toxicology, this research also explores how CPX and AMP influence gut bacteria and how AFB 1 and DEN trigger hepatorenal toxicity through redox and protective pathways. The study compares computational predictions with laboratory findings, identifying STAT3, EGFR, MAPK8, IKBKB, MMP2, MET, and NOS2 as key genes involved in these processes. Molecular docking results indicate that AFB 1 , CPX, and AMP each bind strongly to EGFR (with affinities of − 8. 5, − 7. 7.8, and − 7. 7.6 kcal/mol, respectively), suggesting a potential combined effect on EGFR signalling. These interactions may provide insight into how changes in the gut microbiota contribute to toxicity involving both STAT3 and EGFR. In vivo validation was carried out using male Wistar rats (n = 90, 200g ± 20), divided into nine groups: Group 1 —control (2 mL saline, per os ); Group 2 —AMP (20 mg/kg, per os ); Group 3 —CPX (12. 5 mg/kg, per os ); Group 4 —DEN (200 mg/kg, i. p. ); Group 5 —AFB 1 (2 mg/kg); Group 6 —AMP + DEN; Group 7 —CPX + DEN; Group 8 —AMP + AFB 1 ; Group 9 —CPX + AFB 1 . Two rats from each group were sampled before and after treatment to assess gut microbiota. The findings revealed that DEN, AFB 1 , and combinations with AMP or CPX reduced body, liver, and kidney weights ( p < 0. 05 ). Co- treatments elevated serum transaminase, creatinine, and urea levels, while antioxidant enzyme activity, GSH, and TSH decreased ( p < 0. 05 ). Markers of inflammation, lipid peroxidation, alpha- fetoprotein, and caspase- 3 increased, whereas IL- 10 decreased in the liver and kidney ( p < 0. 05 ). Overall, AMP and CPX exacerbated gut dysbiosis and worsened hepatorenal toxicity with AFB 1 and DEN, heightening the risk of carcinogenesis. Gut microbiota dysbiosis ampicillin ciprofloxacin diethylnitrosamine aflatoxin B1 hepatotoxicity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Introduction The gut microbiome, which is mainly composed of bacteria, plays a vital role in health and disease [ 1 ]. Evidence has shown that over 2000 bacterial species have been identified in the human gut belonging to different phyla, including Bacteroidetes , Firmicutes, Proteobacteria, Fusobacteria, Actinobacteria , Verrucomicrobia , and Cyanobacteria [ 2 – 6 ]. The gut microbiota plays a vital role in humans by supporting gut homeostasis, protecting against pathogen invasion, enhancing immune system development, and producing signalling molecules [ 4 , 7 , 8 ]. Of note, the beneficial gut microbes maintain a fragile equilibrium, which, when disrupted, leads to impaired intestinal mucosal barrier function, inflammation, impaired immunity, behaviour, and metabolic function [ 9 ]. This forms the pathological basis of several diseases, including gut dysbiosis [ 10 , 11 ]. Interestingly, unrestricted use of antibiotic treatment, whether short- or long-term, negatively impacts microbiota health [ 12 – 14 ]. Although, reportedly used to eradicate specific pathogenic bacteria saving millions of lives [ 15 – 17 ], its non-specific action on pathogens result depletion of the normal gut microbiota community [ 12 , 18 , 19 ] including the bifidobacteria, lactobacteria, actinobacteria , and Lachnospiraceae while, causing an increase in the opportunistic and pathogenic bacteria including Enterobacteriaceae, Bacteroidaceae, enterococci , and drug-resistant Escherichia coli [ 17 , 20 ]. These effects are commonly associated with several prescribed antibiotic classes, including beta-lactam antibiotics, aminoglycosides, daptomycin, fluoroquinolones, glycopeptides (teicoplanin and vancomycin) and linezolid [ 21 , 22 ]. While gut dysbiosis remains a potent risk factor for certain diseases, including gastrointestinal diseases, liver disease, diabetes and cancer [ 23 , 24 ]. Its role in carcinogen-exposed individuals (mycotoxins and Nitrosamines) remains unknown. Among well-known carcinogens are aflatoxins, a class of mycotoxins produced predominantly by Aspergillus flavus and Aspergillus parasiticus , which pose a serious health risk to both humans and animals [ 23 , 25 ]. Aflatoxin contamination affects approximately 25% of the global food supply and nearly 40% of food crops in sub-Saharan Africa, thereby placing a hefty burden on developing countries. [ 26 , 27 ]. Over 4 billion people worldwide are exposed to dietary aflatoxins, especially aflatoxin B 1 (AFB 1 ), in peanuts, maize, and tree nuts, which are strongly associated with liver cancer (hepatocellular carcinoma) in humans [ 28 – 30 ]. AFB 1 also causes multiorgan damage, especially the gut, spleen, lungs, brain, liver and kidney, immune system suppression and cancer [ 31 – 34 ] through liver cytochrome P-450 activation, producing a highly reactive metabolite known as AFB 1 -8,9-epoxide [ 35 ] that forms covalent DNA adduction, inducing oxidative stress, inflammation, apoptosis and epigenetic modification [ 36 – 39 ]. Similarly, nitrosamines embrace a broad category of environmental carcinogens in smoked pickled fish, cheese, nitrite-cured meats, dried milk and alcoholic beverages or tobacco smoke, which presents a global concern due to its multiorgan tumorigenic effect [ 40 – 42 ]. Particularly, diethyl nitrosamine (DEN) is associated with reactive oxygen species (ROS), inflammatory activation, impaired apoptosis, and overexpression of G1/S phase regulatory proteins in experimental models [ 43 – 49 ]. Although the carcinogenic effect of AFB 1 and DEN is well established, their individual effects under conditions of unrestricted antibiotic exposure remain poorly understood. Therefore, this study aims to investigate the impact of antibiotic-induced gut microbial imbalances from unrestricted use and its effects on chemical carcinogen exposure, targeting liver and kidney oxidative stress, inflammation, and apoptotic mechanisms in vivo and in silico studies. Materials and Methods Acquisition of Molecular Structures The molecular structures of CPX, AMP, AFB 1 , and DEN were obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov/) using its search function, which provided 2D and 3D molecular structures as well as SMILES notation [50]. Network Toxicology and Molecular Docking We constructed a ligand–target network for Ampicillin (AMP), Ciprofloxacin (CPX), Aflatoxin B 1 (AFB 1 ), and Diethyl nitrosamine (DEN) by combining predicted ligand targets obtained from SwissTargetPrediction (https://www.swisstargetprediction.ch/) accessed on 27th October 2025. Protein–protein interactions (PPI) for the intersecting gene set were retrieved from STRING (v11) and visualised in Cytoscape (v3.9). Hub proteins were identified using CytoHubba (MCC algorithm) and prioritised for structural analysis. Three-dimensional ligand structures were downloaded on 28th October 2025, from PubChem (https://pubchem.ncbi.nlm.nih.gov/) and converted to pdb/pdbqt using BIOVIA (v3.x). Receptor structures were obtained from the RCSB PDB (https://www.rcsb.org/) and accessed on 28th October 2025. Targets lacking were prepared by removing non-essential ligands/waters, adding polar hydrogens at pH 7.4, and converting to pdbqt with MGLTools. Initial rigid docking was performed using PyRx with search exhaustiveness = 16, num_modes = 20, and an energy_range = 4. Grid boxes were centred on co-crystallised ligands where present, or on predicted pockets (CASTp/DoGSite) where absent; box sizes were set between 18–28 Å depending on pocket volume. Docking results were ranked by binding energy and visually inspected in Biovia Discovery Studio (2021). Docked poses were analysed for hydrogen bonds, hydrophobic contacts and interactions with catalytic residues. Docking-derived ligand protein edge weights were integrated back into the PPI network (edge weight ∝ −docking score) in Cytoscape to identify ligand-influenced hubs and enriched pathways. All scripts, parameter files and raw docking/MD outputs are available on request. Toxicity analysis The SMILES notations of AFB 1 and DEN were inserted into the “Predict compound toxicity” module of ProTox 3.0 [51] (https://tox.charite.de/protox3/) to generate toxicity profiles. Similarly, the SMILES notations were submitted to (http://admetmesh.scbdd.com/) to obtain predictions for specific toxicity endpoints[52]. Chemicals, Reagents and Kits Aflatoxin B 1 (1162-65-8), 5,5’-dithiobis-(2-nitrobenzoic acid) (69-78-3), Formalin (590-46-5), Epinephrine (51-43-4), Hydrogen peroxide (H 2 O 2 ) (7722-84-1), O-Dianisidine (119-90-4), Reduced glutathione (GSH) (70-18-8), Sodium-Potassium tartrate (6381-59-5), Sodium azide, Sulfosalicylic acid (5965-83-3), Thiobarbituric acid (TBA) (504-17-6), 2’,7’-dichlorodihydrofluorescin diacetate (4091-99-0), and 1-Chloro-2,4-dinitrobenzene (CDNB) (97-00-7) and Diethyl nitrosamine (55-18-5) were purchased from Sigma-Aldrich Inc. (St Louis, MO, USA). Prof. A.K. Oyelere supplied Ampicillin and Ciproflaxin from Georgia Institute of Technology, USA. Aspartate Aminotransferase (AST) (AS101), Alanine Aminotransferase (ALT) (AL146), Alkaline phosphatase (ALP) (AP307), Urea (UR1068), and Creatinine (CR510) were purchased from VWR, USA. Randox Laboratories, UK. Dipotassium hydrogen phosphate trihydrate (7758-11-4), Potassium Chloride (7447-40-7), Potassium dihydrogen phosphate (7778-77-0) were purchased from AK Scientific, Union City, USA. MacConkey Agar, Nutrient Agar, Centrimide Agar, Mannitol Salt Agar, Eosin Methylene Blue Agar, Salmonella-Shigella Agar, and MRSA were obtained from HI-Media Laboratories, Maharashtra, India. Protein Carbonyl, Rat α-FP (Alpha-Fetoprotein) (E-EL-R00153), Rat IL-10 (Interleukin 10) (E-EL-R0016), and Rat CASP3 (Caspase 3) (E-EL-R0160) were purchased from E-lab Biosciences Company (Wuhan, China). Experimental design Ninety (90) male Albino Wistar rats weighing 200g ± 20 g were sourced from the Faculty of Veterinary Medicine, University of Ibadan, Nigeria, and used for this study. The animals were housed in the Department of Biochemistry Experimental Animal House in spacious plastic cages within a well-ventilated vivarium, maintained under standard laboratory conditions with a 12h/12h light/dark cycle, with the light kept off during dark hours. No researchers entered the animal house during the dark cycle, and the rats had free access to rat feed and water. The animals were acclimatised for one week before the experiment commenced. Animal care and experimental protocols strictly adhered to the guidelines approved by the University of Ibadan Animal Care and Use Research Committee and the ‘Guide for the Care and Use of Laboratory Animals’ published by the National Academy of Science (NAS) and the National Institute of Health. The study protocol received approval from the Care and Use Research Ethics Committee (ACUREC) at the University of Ibadan (UI-ACUREC/068-0524/06). Following the one-week acclimatisation period, the rats were randomly allocated into nine (9) cohorts, each comprising ten (10) rats. The rats were treated with Ampicillin [53] or Ciprofloxacin [54] for two weeks, and from each group, two rats were randomly selected to provide faecal samples from the colon for microbial analysis to assess microbial population counts. On day 15, a single intraperitoneal injection of diethyl nitrosamine [55] and Aflatoxin B 1 [56] was administered, while antibiotic treatment continued for an additional seven days. The animals were sacrificed on day twenty-two, as illustrated in Figure 1 and as outlined below: Group 1: (Control) 2 mL/Kg normal saline per os . Group 2: Ampicillin (AMP) 50 mg/Kg per os . Group 3: Ciprofloxacin (CPX) 12.5 mg/Kg per os . Group 4: Diethylnitrosamine (DEN) 200 mg/Kg i.p . Group 5: Aflatoxin B 1 (AFB 1 ) 2 mg/Kg i.p. Group 6: AMP + DEN : AMP ( 50 mg/Kg) + DEN (200 mg/Kg ; i.p. ). Group 7: CPX + DEN : CPX (12.5 mg/Kg) + DEN (200 mg/Kg ; i.p. ). Group 8: AMP + AFB 1 : AMP (50 mg/Kg) + AFB 1 ( 2 mg/Kg ; i.p. ). Group 9: CPX + AFB 1 : CPX (12.5 mg/Kg) + AFB 1 ( 2 mg/Kg ; i.p. ). . Sample Microbial Analysis Following acclimatisation and before treatment, two animals from each group were randomly chosen for bacterial culture and population analysis. The rats were humanely euthanised, after which colon faecal material was collected aseptically for bacterial culture. 1 g of the colon faecal sample was weighed and diluted in 9 mL of sterile water to produce a 10^-1 dilution. The mixture was vortexed, and 1 mL was transferred into 9 mL of sterile water to create a 10^-2 serial dilution. From this dilution, 0.2 mL was added to a petri dish containing freshly prepared Nutrient Agar, and the sample was gently spread over the media with a sterile glass rod to ensure even distribution. Additionally, 0.1 mL of the 10^-2 dilution was plated onto Eosin Methylene Blue (EMB), MacConkey, Cetrimide, Salmonella-Shigella Agar (SSA), Mannitol Salt Agar (MSA), and Methicillin-resistant Staphylococcus aureus Agar (MRSA) plates. The plates were incubated at 37°C for 24 hours to promote bacterial growth. Once incubation was complete, the number of bacterial colonies on each plate was counted with a colony counter. After 21 days of treatment, the bacterial culture process was repeated using the same procedure. Results were reported as colony-forming units (CFU) per mL. Estimation of Gut Microbial Population Tissue Sample Collection and Biochemical Assay The final body weights of experimental animals were measured on day 21, 24 hours after the last treatment, before exsanguination was performed via the retro-orbital venous plexus to collect blood samples into labelled plain tubes. Rats were then sacrificed by dislocating their cervical vertebrae. Whole blood was allowed to stand at room temperature for 30 minutes, and serum was obtained by centrifugation at 3000 g for 10 minutes in a cold centrifuge at 4°C. Subsequently, serum samples were preserved at -20°C pending routine analysis of enzymes relevant to the liver and kidney. Furthermore, the organs of interest, i.e., the liver and the kidney, were immediately removed, rinsed in ice-cold potassium chloride (KCl) solution, weighed, and recorded, then processed for histological and biochemical tests. Harvested tissue samples (liver and kidney) were rinsed in ice-cold 1.15% KCl solution, blotted with filter paper, and weighed to determine their initial weights. Thereafter, the liver and the kidney samples were sectioned for histological examination and immersed in formalin. The remaining portions of the harvested liver and kidney were homogenised with 0.1 M phosphate buffer (pH 7.4) using a Teflon homogeniser. The homogenates obtained were then centrifuged at 10,000 revolutions per minute (rpm) for 15 minutes in a cold centrifuge (4°C) to obtain the post-mitochondrial fraction. After centrifugation, the supernatants were collected for biochemical and inflammatory analyses. Assessment of Liver and Kidney Function Biomarkers The activity and the level of liver and kidney function biomarkers in the rats were assessed using the Randox™ Laboratory analytical reagent kit. The levels of liver enzymes—Alkaline Phosphatase (ALP), Aspartate Aminotransferase (AST), and Alanine Aminotransferase (ALT)—Creatine and Urea were measured according to the colourimetric methods and protocols provided in the manufacturer's manual, utilising a Molecular Devices Multimodal Spectrophotometer 384 TM (San Jose, CA, USA). The levels of creatinine and urea in the animals' kidneys were also estimated according to the manufacturer's instructions and guidelines. Assessment of rats’ antioxidant biomarkers The activity of antioxidant biomarkers in the supernatant of the liver and kidney of rats was assessed. Superoxide dismutase (SOD) was measured using the Misra and Fridovich method, which involves determining SOD inhibitory activity on the auto-oxidation reaction of adrenaline; 50 µL of sample was added to 2.5 mL of 0.05 M carbonate buffer (pH 10.2) and 0.3 mL of epinephrine in a cuvette, mixed by inversion, with the change in absorbance recorded every 30 seconds for 2 minutes at 480 nm [57]. Glutathione- S -transferase (GST) activity was estimated using the method of Habig et al. [58]. 50 µL of sample was added to 170 µL of the reaction mixture (20 mL phosphate buffer, 0.5 mL reduced glutathione, and 10.5 mL distilled water), and 10 µL of 20 mM 1-chloro-2,4-dinitrobenzene was added to the cuvette. The contents were gently mixed, and the change in absorbance at 340 nm was monitored every 60 seconds for 3 minutes against a reagent blank containing all components except the sample. Glutathione peroxidase (GPx) activity was measured following the method of Rotruck et al. [59], using 50 µL of tissue supernatant mixed with a reaction solution containing 500 µL of potassium phosphate buffer (pH 7.0), 100 µL of NANO3, 200 µL of GSH (4 mM), 100 µL of H₂O₂ (2.5 mM), 500 µL of distilled water, and the sample. The mixture was incubated at 37°C for 3 minutes, then the reaction was stopped by adding 500 µL of 10% TCA and centrifuged at 3000 rpm for 5 minutes. The supernatant was then combined with K₂HPO₄ (0.3 M) and 50 µL of DTNB (0.04%), and absorbance was read at 412 nm after 3 minutes. Reduced glutathione (GSH) levels were estimated using the method of Beutler et al. [60]. Total thiol groups (TSH) were determined according to the method of Hu and Dillard [61], which involves reaction with dithionitrobenzoic acid (DTNB) to produce a yellow compound that absorbs at 412 nm. Assessment of rats’ pro-inflammatory, apoptotic and tumour biomarkers Pro-inflammatory biomarkers, namely Myeloperoxidase and Nitric oxide levels, were evaluated. Myeloperoxidase (MPO) activity, an indicator of polymorphonuclear leukocyte infiltration, was determined using the method described by Trush et al. [57]. MPO activity was measured spectrophotometrically with o-dianisidine (Sigma-Aldrich) and hydrogen peroxide. In the presence of H₂O₂ as an oxidising agent, MPO catalyses the oxidation of o-dianisidine, resulting in a brown-coloured oxidised product with a peak absorbance at 470 nm. The level of nitric oxide was assessed following the method of Green et al. [58]. Nitrite mediates nitrosative modification using Griess reagent—mixed in a 1:1 ratio of sulfanilamide (1%) and N-naphthyl ethylenediamine dihydrochloride (0.1%)—to produce a pink-orange coloured product, with absorbance measured at 550 nm. The oxidative stress biomarker lipid peroxidation (LPO) was determined by measuring the formation of thiobarbituric acid reactive substances (TBARS) in tissue homogenate, using 30% trichloroacetic acid to deproteinise the tissue, which was then mixed with 0.75% thiobarbituric acid (TBA), boiled at 80°C, cooled on ice, and centrifuged at 3000 rpm for 10 minutes. Supernatants were read at 532 nm using the SpectraMax™ 384 multimodal plate reader [59]. Tissue concentrations of the tumour biomarker alpha-fetoprotein (AFP), as well as anti-inflammatory indices interleukin 10 (IL-10) and apoptosis marker caspase 3, were analysed using ELISA kits according to the manufacturer's protocol. Statistical Analysis Data obtained in this study are expressed as means ± SD and analysed using one-way ANOVA and Bonferroni post-hoc test (GraphPad Prism version 10.0 for MacOS, CA, USA). The level of statistical significance was set at *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 versus AMP-, CPX-, DEN-, and AFB 1 -induced rats. Results Network Pharmacology 179 target genes were identified for AFB 1 , DEN, CPX, and AMP, as shown in the Venn diagram and network graph (Fig. 3A and B). Of these, 172 are specific to CPX and AMP, as depicted in the Venn diagram and network graph (Fig. 2A). Seven intersection genes were chosen for further analysis. STAT3, EGFR, MAPK8, IKBKB, MMP2, MET, and NOS2 emerged as the hub targets based on MCC values. The PPI network consisted of seven nodes and fifteen edges. The topological parameters of the PPI network are displayed in Fig. 2D, and E . Enrichment analysis results were filtered using -log 10 (FDR), and the top 20 GO terms selected and shown in Fig. 3 . The results indicated that the targets of the toxicants and antibiotics are involved in biological processes such as responses to oxidative stress, inflammatory response, and regulation of cell communication. The targets are associated with cellular components (CC), such as the membrane raft, receptor complex, and basal plasma membrane. Their molecular functions (MF) include kinase activity, protein kinase binding, and carbohydrate derivative binding. The top 20 KEGG pathway enrichment terms were highlighted in Fig. 3B , with the MAPK Signalling Pathway illustrated in Fig. 4. KEGG analysis revealed that these targets encompass EGFR tyrosine kinase inhibitor resistance, chemical carcinogenesis, reactive oxygen species, and the MAPK signalling pathway. Molecular Docking Molecular docking was performed to evaluate the binding affinities and interaction modes of Aflatoxin B 1 (AFB 1 ), Ciprofloxacin (CPX), Ampicillin (AMP), and Diethylnitrosamine (DEN) with Epidermal Growth Factor Receptor (EGFR) and Signal Transducer and Activator of Transcription 3 (STAT3). The binding interactions are illustrated in Figs 5A–B . In agreement with their docking scores, all ligands had high binding affinities for EGFR (AFB 1 = –8.5 kcal/mol, CPX = –7.8 kcal/mol, AMP = –7.6 kcal/mol, DEN = –4.8 kcal/mol). Within the EGFR active pocket, CPX demonstrated robust binding, forming carbon-hydrogen interactions with Met769, Leu768, and Asp831, as well as conventional hydrogen bonds with Lys721, Thr766, and Gln767 ( Fig. 5A 1 ). A conventional hydrogen bond with Thr766 stabilises the firmly bound AFB 1 ( Fig. 5A 2 ). DEN exhibited a relatively weak interaction, forming a single hydrogen bond with Arg812 ( Fig. 5A 4 ). AMP interacted with Lys721 and Cys773 by typical hydrogen bonds ( Fig. 5A 3 ). Based on these interactions, AMP, CPX, and AFB 1 may occupy catalytically significant regions of EGFR, thereby altering receptor function and downstream proliferative signalling. Binding of the ligands to STAT3 showed the ligand docking scores (AFB 1 = -6.4kcal/mol, CPX = -6 kcal/mol, AMP = -5.7 kcal/mol, DEN = –4kcal/mol). CPX displayed strong binding characterised by a conventional hydrogen bond with Asn359 and a carbon-hydrogen bond with Glu397 ( Fig. 5B 1 ). AFB 1 exhibited hydrogen bonding with Arg152 and additional carbon-hydrogen bonding with Asn265 ( Fig. 5B 2 ), while AMP formed stable hydrogen bonds with Asn359 and Glu159 ( Fig. 5B 3 ). In contrast, DEN failed to form any significant stabilising interactions, instead displaying a repulsive bond within the docking pocket ( Fig. 5B 4 ). The absence of favourable interactions between DEN and STAT3 supports its weaker binding affinity observed in docking simulations. Collectively, these results indicate that AFB 1 , CPX, and AMP exhibit strong and stable binding to both EGFR and STAT3, suggesting potential interference with signalling cascades regulating oxidative stress, inflammation, and cell proliferation. DEN, with its lower binding affinity and minimal stabilising interactions, may contribute to hepatocarcinogenesis through indirect or metabolic pathways rather than direct receptor engagement. Molecular structure and toxicity prediction of AFB 1 and DEN The 3D and 2D molecular structures of AFB 1 and DEN were retrieved from PubChem (Fig. 6a and 6b). Toxicological profiling by ProTox 3.0 revealed toxicity predictions and physicochemical features for AFB 1 and DEN, with AFB 1 exhibiting a higher acute toxicity profile (LD 50 = 3 mg/kg, Class 1) than DEN (LD 50 = 200 mg/kg, Class 3). Both compound predictions demonstrated 100% accuracy and a mean structural similarity of 100% to the reference compounds ( Fig. 6 ). Analysis via ADMETlab provided a comprehensive profile of 13 physicochemical properties for AFB 1 and DEN. This included specified upper and lower limits for properties such as molecular weight and octanol-water partition coefficient (logP), as well as compound properties ( Fig. 6a and 6b ). The compounds exhibited strong carcinogenicity and mutagenicity signals ( Table 1 ). Gut microbial colonies were adversely affected by ampicillin and ciprofloxacin treatment and worsened by co-treatment with diethyl nitrosamine and aflatoxin B 1 . Pre-treatment gut microbial counts and diversity are similar to those typically found in a rodent's gut. The population of Lactobacillus, which is associated with healthy gut function, was higher in control rodents than in those treated with antibiotics. Antibiotic treatment reduced beneficial Lactobacillus bacteria. This reduction was further intensified by co-treatment with AFB1 and DEN, as shown in Supplementary Table 1 . A decline in Lactobacillus levels can lead to the overgrowth of pathogenic bacteria, disruption of the gut barrier (leaky gut), altered metabolism, and increased inflammation, potentially resulting in various diseases. Refer to Supplementary Table 2 . Diethylnitrosamine and aflatoxin B 1 resulted in reduced body weight and lower organ-to-body weight indices in rats co-administered with ampicillin and ciprofloxacin. As depicted in Table 2 , there was a significant increase in body weight and in organ-to-body weight ratio somatic indices of rats across the groups following 21-day repeated exposure to antibiotics (AMP, CPX) and co-exposure to single doses of DEN and AFB 1 . Compared with control, treatment with AMP, CPX, and AMP + DEN showed a significant decrease in final body weight, with a marked reduction in weight gain across all groups; the effect was most pronounced in AMP + DEN, CPX + DEN, and CPX + AFB 1 . Liver weight in groups treated with DEN, CPX + DEN, CPX + AFB1, AMP + DEN, CPX + DEN, AMP + AFB1, and CPX + AFB 1 was significantly increased, while CPX, AFB 1 , AMP + DEN, CPX + DEN, AMP + AFB 1 and CPX + AFB 1 showed a significant increase in kidney weight when compared with control. Interestingly, all treated groups demonstrated significant increase in both liver and kidney relative weight when compared with the control Table 2: Body weight change and organosomatic of rats treated with AMP, CPX for 21 days and a single intraperitoneal dose of DEN and AFB 1 on day 15 Control AMP CPX DEN AFB 1 AMP + DEN CPX + DEN AMP + AFB 1 CPX + AFB 1 Initial body weight (g) 204.2±9.91 192.2±5.26 196.3±8.21 211.7±8.98 217±8.27 216.8±6.59 215±8.94 211.2±6.94 220±10.88 Final body weight (g) 234.7±12.40 206.2±10.25* 197.7±8.21*** 208.8±15.83 217.7±11.59 205.7±20.36* 210.2±12.8 216.8±7.33 211.3±15.49 Weight gain (g) 30.5±17.21 14.0±11.22 1.3±6.38** -2.8±8.32*** 0.7±7.31** -11.2±16.77**** -4.8±8.57*** 5.7±8.91* -8.7±16.65**** liver weight (g) 4.7±0.83 5.3±0.26 5.5±0.26 5.6±0.13* 5.4±0.53 5.3±0.14 6.2±0.09**** 5.4±0.20 5.6±0.48* Kidney weight (g) 1.1±0.30 1.4±0.04 1.5±0.09** 1.3±0.31 1.5±0.12** 1.5±0.11* 1.5±0.22** 1.5±0.06** 1.5±0.14** Relative liver weight (%) 2.0±0.31 2.6±0.20* 2.8±0.13**** 2.7±0.21*** 2.5±0.27* 2.6±0.28** 2.9±0.19**** 2.5±0.14* 2.7±0.33*** Relative kidney weight (%) 0.5±0.14 0.7±0.04* 0.8±0.03*** 0.6±0.15 0.7±0.08** 0.7±0.11*** 0.7±0.13*** 0.7±0.05** 0.7±0.07** Control (Normal Saline 2 mL/kg, n=6), AMP (20 mg/kg, n=6), CPX (12.5 mg/kg, n=6), DEN (200 mg/kg, n=6), AMP + DEN (20 mg/kg + 200 mg/kg, n=6), CPX + DEN (12.5 mg/kg + 200 mg/kg, n=6), AMP + AFB 1 (20 mg/kg + 2 mg/kg, n=6), CPX + AFB 1 (12.5 mg/kg + 2 mg/kg, n=6). Values are expressed as mean ± SD. * indicates values that differ significantly (p < 0.05) from the control. AMP, Ampicillin. CPX, Ciprofloxacin; DEN, Diethylnitrosamine; AFB 1 , Aflatoxin B 1 . The impact of diethylnitrosamine and aflatoxin B 1 on serum hepatic and renal function activities in rats co-treated with ampicillin and ciprofloxacin The effect of DEN and AFB 1 on the serum hepatic and renal function of rats cotreated with AMP and CPX is shown in Fig 7 . Compared with the control, there is an increase (p < 0.05) in the activities of ALP, AST, and ALT in rats treated with 20 mg/Kg AMP and 12.5 mg/Kg CPX ( Fig. 7) . Compared with the DEN and AFB 1 groups, there is an increase (p<0.05 ) in hepatic transaminases activities—ALP, AST, and ALT—in rats cotreated with 20 mg/Kg AMP + 200 mg/Kg DEN, 12.5 mg/Kg CPX + 200 mg/Kg DEN, 20 mg/Kg AMP + 2 mg/Kg AFB 1, and 12.5 mg/Kg CPX + 2 mg/Kg AFB 1 . Compared with the control, serum urea and creatinine levels are increased (p < 0.05) in rats treated with 20 mg/Kg AMP and 12.5 mg/Kg CPX ( Fig. 7) . Additionally, compared to the DEN and AFB 1 groups, serum urea and creatinine levels are elevated (p<0.05) in rats cotreated with 20 mg/Kg AMP + 200 mg/Kg DEN, 12.5 mg/Kg CPX + 200 mg/Kg DEN, 20 mg/Kg AMP + 2 mg/Kg AFB 1 , and 12.5 mg/Kg CPX + 2 mg/Kg AFB 1 . This result indicates kidney damage. The impact of diethylnitrosamine and aflatoxin B 1 on enzymatic antioxidant biomarkers in rats co-treated with Ampicillin and Ciprofloxacin. The effect of DEN and AFB 1 on the activities of antioxidant enzymes: Superoxide Dismutase (SOD), Glutathione- s -transferase (GST), Glutathione Peroxidase (GPX) and Reduced Glutathione (GSH), Total Sulfhydryl (TSH) in rats cotreated with AMP and CPX is shown in Fig 8-9 . Compared with the control, the antibiotics-only treatment (20 mg/Kg AMP and 12.5 mg/Kg CPX) significantly reduced the levels of liver and kidney antioxidant biomarkers (SOD, GST, GPX, GSH, and TSH). Meanwhile, there was a greater decrease ( p<0.05 ) in the activities of SOD and GST (Fig 8), GPX, GSH, and TSH (Fig 8) in experimental rats co-treated with antibiotic and carcinogen cotreated groups (20 mg/Kg AMP + 200 mg/Kg DEN, 12.5 mg/Kg CPX + 200 mg/Kg DEN, 20 mg/Kg AMP + 2 mg/Kg AFB 1 , 12.5 mg/Kg CPX + 2mg/Kg AFB 1 ) compared with the control groups . The impact of diethylnitrosamine and aflatoxin B 1 on oxidative stress and pro-inflammatory biomarkers in rats co-treated with ampicillin and ciprofloxacin The effect of DEN and AFB 1 on pro-inflammatory biomarkers: Lipid Peroxidation (LPO) level, Myeloperoxidase (MPO) activity, and Nitric Oxide (NO) level in rats treated with AMP and CPX is illustrated in Fig 10 and Fig 11A . Antibiotic-only treatment (20 mg/Kg AMP and 12.5 mg/Kg CPX) elevated MPO, NO ( Fig. 9 ), and LPO ( Fig. 10A ) levels in the liver and kidneys compared with control groups. Likewise, rats cotreated with these carcinogens exhibited a greater increase ( p<0.05 ) in the levels of MPO, NO, and LPO (20 mg/Kg AMP + 200 mg/Kg DEN, 12.5 mg/Kg CPX + 200 mg/Kg DEN, 20 mg/Kg AMP + 2 mg/Kg AFB 1 , 12.5 mg/Kg CPX + 2 mg/Kg AFB 1 ) when compared with controls. The impact of diethylnitrosamine and aflatoxin B 1 on anti-inflammatory cytokines in rats co-treated with ampicillin and ciprofloxacin The effect of DEN and AFB 1 on liver and kidney anti-inflammatory cytokine: Interleukin 10 (IL-10) levels in rats treated with AMP and CPX is shown in Fig 12. Compared with the untreated control, there is a decrease ( p<0.05 ) in IL-10 levels in the treated control groups: 20 mg/Kg AMP, 12.5 mg/Kg CPX, 200 mg/Kg DEN, 2 mg/Kg AFB 1, and in the co-treated groups: 20 mg/Kg AMP + 200 mg/Kg DEN, 12.5 mg/Kg CPX + 200 mg/Kg DEN, 20 mg/Kg AMP + 2 mg/Kg AFB 1 , 12.5 mg/Kg CPX + 2 mg/Kg AFB 1 . The impact of diethylnitrosamine and aflatoxin B 1 on tumour biomarkers in rats co-treated with ampicillin and ciprofloxacin The effect of DEN and AFB 1 on the liver and kidney tumour biomarker alpha-fetoprotein (α-FP) levels in rats co-treated with AMP and CPX is shown in Fig. 11B. Compared with the untreated control, there is an increase ( p<0.05 ) in the level of α-FP in the antibiotics-only groups (20 mg/Kg AMP, 12.5 mg/Kg CPX, 200 mg/Kg), carcinogen-treated groups (DEN, 2 mg/Kg AFB 1 ), and the co-treated cohorts: 20 mg/Kg AMP + 200 mg/Kg DEN, 12.5 mg/Kg CPX + 200 mg/Kg DEN, 20 mg/Kg AMP + 2 mg/Kg AFB 1 , 12.5 mg/Kg CPX + 2 mg/Kg AFB 1 . The effect of diethylnitrosamine and aflatoxin B 1 on pro-apoptotic biomarkers in rats co-treated with ampicillin and ciprofloxacin. The effect of DEN and AFB 1 on liver and kidney pro-apoptotic biomarkers, specifically caspase 3 activity in rats treated with AMP and CPX, as well as in co-treated experimental rats, is shown in Fig 12B. Compared to the untreated control, there is an increase ( p<0.05 ) in Caspase 3 activity in the treated control groups: 20 mg/Kg AMP, 12.5 mg/Kg CPX, 200 mg/Kg DEN, 2 mg/Kg AFB 1, and in the co-treated groups: 20 mg/Kg AMP + 200 mg/Kg DEN, 12.5 mg/Kg CPX + 200 mg/Kg DEN, 20 mg/Kg AMP + 2 mg/Kg AFB 1 , 12.5 mg/Kg CPX + 2 mg/Kg AFB 1 . Discussion Antibiotics are major disruptors of gut microbiota. Oral antibiotics can alter the gut microbiota by disrupting interactions between the normal gut microbiota and opportunistic and pathogenic bacteria, thereby causing dysbiosis e. Shi et al. examined 16S rRNA gene sequences to assess the effects of ampicillin on colonic microbiota diversity, showing a significant reduction in total microbial numbers [ 60 ]. Common carcinogens, including Aflatoxin (AFB 1 ) [ 61 – 63 ] and Diethylnitrosamine (DEN) [ 64 , 65 ], have been identified as potent risk factors for human hepatocarcinogenesis. Molecular docking and network toxicology were used to investigate how commonly misused antibiotics (ciprofloxacin, ampicillin) and dietary hepatocarcinogens (AFB 1 , DEN) influence inflammatory and pro-tumour signalling networks in the liver. Network analysis of shared targets identified a pro-inflammatory/pro-tumorigenic module (IKBKB, NOS2, MAPK8, STAT3), along with growth-promoting receptors (EGFR, MET) and the matrix remodeller MMP2. This indicates that antibiotic- induced gut dysbiosis may sensitise the liver to AFB 1 /DEN- induced genotoxicity [ 66 ] by activating NF- κB/IKKβ signalling and iNOS- mediated nitrosative stress [ 67 ], initiating JNK (MAPK 8) stress responses, and engaging EGFR/MET- STAT 3 survival pathways that support the proliferation of damaged hepatocytes [ 68 ]. Additionally, the relatively high docking affinities of AFB 1 (–8.8 kcal/mol), CPX (–7.8 kcal/mol), and AMP (–7.7.6 kcal/mol) toward EGFR imply potential synergistic effects in modulating EGFR-mediated signalling pathways. These interactions might increase hepatocyte susceptibility to inflammation and neoplastic transformation following antibiotic- induced dysbiosis. The weak binding of DEN (–4.4 kcal/mol) to both EGFR and STAT3 suggests its toxicity depends less on direct receptor engagement and more on metabolic activation via cytochrome P450 enzymes (e.g., CYP2E1), as supported by the literature [ 67 , 69 ]. Notably, antibiotics may indirectly worsen DEN toxicity by disrupting gut microbial balance, reducing microbial metabolites such as short-chain fatty acids (SCFAs), which normally protect hepatic health, and promoting inflammatory responses through NOS2- mediated nitrosative stress. Moreover, network enrichment identified MMP-2 and MET , both of which are linked to extracellular matrix degradation and oncogenic transformation, suggesting that chronic exposure to antibiotics and toxins may accelerate hepatic fibrosis and tumour progression. Complementing these network interactions, in silico ADMET profiling using ProTox-3.0 and ADMETlab [ 52 ] further elucidated the toxicological profiles of AFB 1 and DEN (Table 3, Figs. 13 and 14). Predictive modelling revealed distinct acute oral toxicity classes (Class 1 for AFB 1 with a predicted LD 50 of 3 mg/kg; Class 3 for DEN with a predicted LD 50 of 200 mg/kg), along with high probabilities for carcinogenicity (AFB 1 : 0. 68; DEN: 0. 99) and mutagenicity (AFB 1 : 0. 95; DEN: 0. 96) [ 37 , 70 – 72 ]. Their physicochemical properties, especially lipophilicity (logP = 2. 28 for AFB 1 and 1. 01 for DEN) and molecular weights (312. 27 Da and 102.14. 14 Da, respectively), suggest favourable intestinal absorption and systemic distribution, providing a computational basis for the observed multi- organ (hepatorenal) damage and increased carcinogenesis risk in vivo . In vivo experimental validation further supports a mechanistic link between microbial disruption and increased hepatocarcinogenesis in animals exposed to antibiotics and carcinogens, suggesting a potential rise in inflammatory and nitrosative stress genes. Findings showed reduced total colonic bacterial populations following pre-treatment with ampicillin (AMP) or ciprofloxacin (CPX) alone in experimental rats, as well as in groups co-treated with carcinogens (DEN and AFB 1 ). Although specific colonic microbiota diversity was not identified, these findings corroborate earlier studies indicating antibiotic-induced gut dysbiosis [ 60 , 73 , 74 ]. The results also indicated decreased body weights in the co-treated rats, with no change in organ-to-body weight ratios. This suggests potential toxicological effects on the liver and kidney, as alterations in organ weights are commonly used to assess chemically induced organ injury and toxicity [ 75 ]. Liver injury markers, including hepatic transaminase activities (ALP, AST, and ALT), were elevated in all groups individually or co-exposed to antibiotics and carcinogens (DEN and AFB 1 ) compared to controls, indicating more pronounced hepatic damage in the co-treated groups. Similar effects were observed in kidney function biomarkers (urea and creatinine), implying oxidative injury to kidney cells, especially in co-treated groups. Our findings align with earlier reports showing significantly higher levels of these markers following individual exposure to AMP, CPX, DEN, and AFB 1 , with aggravated hepatic and renal injuries likely due to the effects of AMP and CPX treatments [ 76 – 80 ]. Oxidative damage to tissues is linked to an imbalance between pro-oxidants and antioxidants [ 81 ]. In this study, rats pre-treated with ampicillin and ciprofloxacin exhibited reduced hepatic and renal activities of SOD, GSH, GPx, GST, and TSH (p < 0.05). These effects were more pronounced in co-treated groups than in groups exposed to DEN or AFB 1 alone. These enzymatic and non-enzymatic antioxidants play key roles in neutralising free radicals; their reduction indicates impaired antioxidant defences and an accumulation of free radicals, which can cause potential damage to DNA, proteins, and carbohydrates, disrupting cellular functions [ 82 ]. Oxidative damage to DNA is indicated by increased membrane lipid peroxidation levels in tissues [ 83 , 84 ]. Findings showed elevated levels of lipid peroxides and nitric oxide (NO) in the livers and kidneys of rats co-treated with DEN and AFB 1 compared to controls, indicating that free radical generation exceeded the capacity of antioxidant enzymes to detoxify. Studies suggest that NO levels are a key factor in inflammation and nitrosative stress mediated through superoxide anion, which can disrupt the structure of macromolecules such as proteins, thereby impairing their functions [ 85 , 86 ]. The increased hepatic and renal NO levels correlated with higher myeloperoxidase (MPO) activity, an indicator of macrophage and neutrophil infiltration [ 87 ], which plays a crucial role in immune responses [ 88 – 90 ]. MPO has been reported to catalyse the formation of reactive oxygen and nitrogen species in the presence of H 2 O 2 [ 91 , 92 ]. Our findings suggest activation of hepatic and renal inflammatory signalling following co-treatment with antibiotics and carcinogens (DEN and AFB 1), alongside a suppression of anti-inflammatory cytokines such as IL-10. Furthermore, the present study revealed a significant increase in caspase-3 activity in the liver and kidneys of rats co-treated with DEN and AFB 1, indicating that excessive cell death [ 93 , 94 ]. This finding supports the elevated alpha-fetoprotein (AFP) levels observed across all treated groups, which were more pronounced in the co-treated rats, indicating early severity of tissue damage and a tumourigenic event [ 95 , 96 ]. Although specific markers of tumourigenic signalling, including angiogenesis, metabolic reprogramming, immune evasion, and genetic and epigenetic alterations, were not assessed. Findings from this study suggest that antibiotic and carcinogen co-exposure may exacerbate tumourigenesis signalling mechanisms. These observations provide a rationale for future studies to further elucidate the molecular pathways underlying antibiotic-carcinogen interactions in cancer development. Antibiotic administration, such as AMP and CPX, decreased gut bacterial populations, thereby worsening carcinogen (DEN and AFB1)- induced hepatorenal damage by impairing hepatic and renal function, reducing antioxidant defence mechanisms, increasing oxidative stress and inflammation, and promoting excessive apoptosis and tumourigenic signalling pathways. These findings highlight the potentiating effect of combined exposure to ampicillin and ciprofloxacin on hepatorenal toxicity caused by diethylnitrosamine and aflatoxin B 1 . Declarations Ethical Approval This study was approved by the Animal Care and Use Research Ethics Committee of the University of Ibadan (UI-ACUREC) under approval number UI-ACUREC/068-0524/06. All procedures were conducted in compliance with applicable guidelines and regulations, and in accordance with the ARRIVE guidelines (https://www.arriveguidelines.org) for reporting animal research. Funding This research was conducted without a specific grant or financial support from any public, commercial, or non-profit funding agency. Credit authorship contribution statement SO, AKO, JC and DAB: Conceptualisation, Methodology, Supervision. DAB, JC, VOE, OMO, and EMP : Project administration, Methodology, and investigation . DAB, JC, VOE, JOB, OMO, SO, AKO and EMP : Data curation, Formal analysis, Writing – original draft, Writing – review and editing. Declaration of Competing Interest The authors declare no known financial conflicts of interest or personal relationships that could have influenced the work presented in this paper. Data Availability Statement The data generated in the current study are available from the corresponding author upon request. Use of Generative AI Grammarly and Microsoft Co-Pilot were used for language editing, along with the Gemini Pro version. 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Pattison, D.I., M.J. Davies, and C.L. Hawkins, Reactions and reactivity of myeloperoxidase-derived oxidants: differential biological effects of hypochlorous and hypothiocyanous acids. Free Radic Res, 2012. 46 (8): p. 975–95. Rayner, B.S., D.T. Love, and C.L. Hawkins, Comparative reactivity of myeloperoxidase-derived oxidants with mammalian cells. Free Radic Biol Med, 2014. 71 : p. 240–255. Grayfer, L., et al., Characterization and functional analysis of goldfish (Carassius auratus L.) interleukin-10. Mol Immunol, 2011. 48 (4): p. 563–71. Fesik, S.W. and Y. Shi, Structural biology. Controlling the caspases. Science, 2001. 294 (5546): p. 1477–8. Kim, H., M. Jang, and E. Kim, Exploring the Multifunctional Role of Alpha-Fetoprotein in Cancer Progression: Implications for Targeted Therapy in Hepatocellular Carcinoma and Beyond. Int J Mol Sci, 2025. 26 (10). Wang, S., et al., Alpha-fetoprotein acts as a novel signal molecule and mediates transcription of Fn14 in human hepatocellular carcinoma. J Hepatol, 2012. 57 (2): p. 322–9. Tables Table 1 and 3 are not available in this version. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTables12GutMicrobialAnalysis.doc Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9094434","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":612045170,"identity":"4cf67868-b55f-4f65-9853-83fd43fb74a3","order_by":0,"name":"Solomon Owumi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAt0lEQVRIiWNgGAWjYDACZiBOqDgAZh94QLyWMwcYeEBaEoi2ibENooWBKC3y7czPPjycd0fOXuzwQ6AtdnK6DYQsaGYznpG47Zkxj3SaAVBLsrHZAQJamJl5mBkStx1O7JFOAGk5kLiNkBY2sJY5IC3pH4jTwgPW0gDSkkOkLRLMbMYMCccOG/Pczik4kGBAhF/k+w8/ZvxRc1iOfXb65g8fKuzkCGpBAwakKR8Fo2AUjIJRgAMAAL7AP6rXmFpjAAAAAElFTkSuQmCC","orcid":"","institution":"University of Ibadan","correspondingAuthor":true,"prefix":"","firstName":"Solomon","middleName":"","lastName":"Owumi","suffix":""},{"id":612045171,"identity":"8a14130f-18e0-4025-ac50-5a4baa1a3882","order_by":1,"name":"Dooshima, A. Bagu","email":"","orcid":"","institution":"University of Ibadan","correspondingAuthor":false,"prefix":"","firstName":"A.","middleName":"Bagu","lastName":"Dooshima","suffix":""},{"id":612045172,"identity":"08c21ca6-1c10-4886-8e9a-3633841e18aa","order_by":2,"name":"Joseph Chimezie","email":"","orcid":"","institution":"University of Ibadan","correspondingAuthor":false,"prefix":"","firstName":"Joseph","middleName":"","lastName":"Chimezie","suffix":""},{"id":612045173,"identity":"d23cfc23-da92-4baf-b691-1d1dcf465cfd","order_by":3,"name":"Jesutosin O. Babalola","email":"","orcid":"","institution":"University of Ibadan","correspondingAuthor":false,"prefix":"","firstName":"Jesutosin","middleName":"O.","lastName":"Babalola","suffix":""},{"id":612045174,"identity":"4f667aba-958b-4b6e-babb-9bac74ffaa80","order_by":4,"name":"Victor O. Eso","email":"","orcid":"","institution":"University of Ibadan","correspondingAuthor":false,"prefix":"","firstName":"Victor","middleName":"O.","lastName":"Eso","suffix":""},{"id":612045175,"identity":"ae1d049e-4d95-4d09-8003-befdd3e2baf8","order_by":5,"name":"Oluwaseun, M. Owolabi","email":"","orcid":"","institution":"University of Ibadan","correspondingAuthor":false,"prefix":"","firstName":"M.","middleName":"Owolabi","lastName":"Oluwaseun","suffix":""},{"id":612045176,"identity":"8f9ce4de-a3a6-437c-90bb-e8e4a3288ba7","order_by":6,"name":"Esther, M. Pius","email":"","orcid":"","institution":"University of Ibadan","correspondingAuthor":false,"prefix":"","firstName":"M.","middleName":"Pius","lastName":"Esther","suffix":""},{"id":612045177,"identity":"8751c4a4-649b-4696-a64a-050c60032d3e","order_by":7,"name":"Adegboyega, K. Oyelere","email":"","orcid":"","institution":"Georgia Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"K.","middleName":"Oyelere","lastName":"Adegboyega","suffix":""}],"badges":[],"createdAt":"2026-03-11 12:50:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9094434/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9094434/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105566254,"identity":"f6ace8ec-6ef8-4fcb-be6e-4b32cc0bb77a","added_by":"auto","created_at":"2026-03-27 12:55:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":846002,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental protocol of Aflatoxin B\u003csub\u003e1\u003c/sub\u003e/DEN and CPX/AMP co-exposure to adult male Wistar rats for 28 consecutive days.\u0026nbsp;\u003cem\u003eCreated by\u0026nbsp;\u003c/em\u003eDooshima using BioRender, https://app.biorender.com/\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-9094434/v1/da84fe7b165ccaf4d0df5f6b.png"},{"id":105509508,"identity":"1a72aa4d-fca4-476f-aa47-278a7d01cc96","added_by":"auto","created_at":"2026-03-26 20:11:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1642464,"visible":true,"origin":"","legend":"\u003cp\u003eProtein-protein interaction (PPI) network of genes and hub gene identification in DEN and AFB\u003csub\u003e1\u003c/sub\u003e-induced hepatotoxicity. (A) Venn diagram showing the overlap between genes related to antibiotics (CPX and AMP) and (AFB\u003csub\u003e1\u003c/sub\u003e and DEN). (B) The network diagram of CPX \u0026amp; AMP with 179 targets, where the red diamond represents CPX \u0026amp; AMP, the blue parallelogram denotes the targets, and the edges indicate the association relationships between CPX \u0026amp; AMP and the targets. (C) The network diagram of AFB\u003csub\u003e1\u003c/sub\u003e \u0026amp; DEN with 61 targets, where the blue rectangle represents AFB\u003csub\u003e1\u003c/sub\u003e \u0026amp; DEN, the blue parallelogram denotes the targets, and the edges indicate the association relationships between AFB\u003csub\u003e1\u003c/sub\u003e \u0026amp; DEN and the targets. (D) Protein-protein interaction between the target genes. (E) The top target clustering, with node sizes indicating MCC ranking values, shows that the targets are ordered from darkest to lightest, clockwise.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-9094434/v1/585c10dfb2c019c82cb095c7.png"},{"id":105567004,"identity":"694d39bb-cd1e-4296-989c-8340feda77f4","added_by":"auto","created_at":"2026-03-27 12:58:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1353048,"visible":true,"origin":"","legend":"\u003cp\u003eGene ontology (GO) and pathway enrichment functional analysis of antibiotics-toxicants targets with a focus on their molecular functions (A), KEGG pathways (B), biological processes (C), and cellular components (D). The size of the dots indicates the number of enriched genes, and the colour of the dots indicates the significance of the fold enrichment and the false discovery rate (FDR), with red representing the most significant in all panels.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-9094434/v1/48188c6c65f98355c75069ca.png"},{"id":105567041,"identity":"879df5e5-14db-486b-9091-43305fef0c2e","added_by":"auto","created_at":"2026-03-27 12:58:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":509978,"visible":true,"origin":"","legend":"\u003cp\u003eKEGG pathway showing the genes involved in the MAPK signalling pathway. Red boxes highlight the genes impacted in this pathway.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-9094434/v1/1e4a753d6f129e34e5e4ed6b.png"},{"id":105567016,"identity":"1de5ebe0-efaf-4475-b402-d5d24b9b995e","added_by":"auto","created_at":"2026-03-27 12:58:01","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":241185,"visible":true,"origin":"","legend":"\u003cp\u003eIdentification of the 2D binding modes of AFB\u003csub\u003e1\u003c/sub\u003e, DEN, CPX, and AMP with EGFR and STAT3. (A-B)\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-9094434/v1/6595f3649d06acdac6986f2e.png"},{"id":105509506,"identity":"841b5e43-1d29-496d-b4dc-12de96cd6955","added_by":"auto","created_at":"2026-03-26 20:11:35","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":419382,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea: \u003c/strong\u003eMolecular structure and toxicity prediction of AFB\u003csub\u003e1\u003c/sub\u003e. (A) 3D structure of AFB\u003csub\u003e1\u003c/sub\u003e; (B) 2D structure of AFB\u003csub\u003e1\u003c/sub\u003e; (C) Evaluation of physicochemical properties and toxicity prediction of AFB\u003csub\u003e1\u003c/sub\u003e based on ProTox 3.0; (D) ADMETlab analysis of the physicochemical properties, including upper limit, lower limit, and compound properties of AFB\u003csub\u003e1\u003c/sub\u003e (logp, Partition Coefficient; MV, Molecular Weight; nRig, Number of Rigid Bonds; fChar, Formal Charge; nHet, Number of Heteroatoms; MaxRing, Maximum Ring Size; nRing, Number of Rings; nRot, Number of Rotatable Bonds; TPSA, Topological Polar Surface Area; nHD, Number of Hydrogen Bond Donors; nHA, Number of Hydrogen Bond Acceptors; logD, Distribution Coefficient; logS, Aqueous Solubility).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb: \u003c/strong\u003eMolecular structure and toxicity prediction of DEN. (A) 3D structure of DEN; (B) 2D structure of DEN; (C) Evaluation of physicochemical properties and toxicity prediction of DEN based on ProTox 3.0; (D) ADMETlab analysis of the physicochemical properties, including upper limit, lower limit, and compound properties of DEN (logp, Partition Coefficient; MV, Molecular Weight; nRig, Number of Rigid Bonds; fChar, Formal Charge; nHet, Number of Heteroatoms; MaxRing, Maximum Ring Size; nRing, Number of Rings; nRot, Number of Rotatable Bonds; TPSA, Topological Polar Surface Area; nHD, Number of Hydrogen Bond Donors; nHA, Number of Hydrogen Bond Acceptors; logD, Distribution Coefficient; logS, Aqueous Solubility).\u003c/p\u003e","description":"","filename":"FIg6.png","url":"https://assets-eu.researchsquare.com/files/rs-9094434/v1/bc647c7ab730ba14690848f7.png"},{"id":105509515,"identity":"1e15cbfc-37d5-45fa-b887-c596e1aa8c15","added_by":"auto","created_at":"2026-03-26 20:11:35","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1554524,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA: \u003c/strong\u003eThe effect of co-exposure to DEN and AFB1 on hepatic transaminase activities in the serum of rats treated with AMP and CPX. Control, (2 mL/kg); AMP, 20 mg/kg; CPX, 12.5 mg/kg; DEN, 200 mg/kg; AFB1, 2 mg/kg; AMP + DEN (20 + 200 mg/kg); CPX + DEN (12.5 + 200 mg/kg); AMP + AFB1 (20 + 2 mg/kg); CPX + AFB1 (12.5 + 2 mg/kg). Values are expressed as mean ± SD for eight rats per group. Connecting lines denote comparisons between groups, with significance set at (p\u0026lt;0.05); * to **** indicate levels of significance; ns: not significant. AFB1, Aflatoxin B1; CPX, Ciprofloxacin; AMP, Ampicillin; DEN, Diethylnitrosamine; ALP, Alkaline Phosphatase; AST, Aspartate aminotransferase; ALT, Alanine aminotransferase.\u003c/p\u003e","description":"","filename":"Fig7.png","url":"https://assets-eu.researchsquare.com/files/rs-9094434/v1/ef78f496410dabaf5cf7826f.png"},{"id":105566729,"identity":"acc5e6cd-12c1-4774-bbad-c8b979aa6256","added_by":"auto","created_at":"2026-03-27 12:57:07","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1363113,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of co-exposure to DEN and AFB1 on the antioxidant enzymes in rats treated with AMP and CPX. The control group received normal saline (2 mL/kg), AMP at 20 mg/kg, CPX at 12.5 mg/kg, DEN at 200 mg/kg, and AFB1 at 2 mg/kg. Treatment groups included AMP+DEN (20+200 mg/kg), CPX+DEN (12.5+200 mg/kg), AMP+AFB1 (20+2 mg/kg), and CPX+AFB1 (12.5+2 mg/kg). Values are expressed as mean ± SD for eight rats per group. Connecting lines compare groups, with significance at (p\u0026lt;0.05); * to **** indicate significance levels; ns: not significant. AFB1: Aflatoxin B1; CPX: Ciprofloxacin; AMP: Ampicillin; DEN: Diethylnitrosamine; SOD: Superoxide dismutase; GST: Glutathione S-transferase.\u003c/p\u003e","description":"","filename":"Fig8.png","url":"https://assets-eu.researchsquare.com/files/rs-9094434/v1/d9b9442a0d2f8800d7659458.png"},{"id":105509510,"identity":"2cff02a9-1879-496a-b1a8-89f2a6878300","added_by":"auto","created_at":"2026-03-26 20:11:35","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":1463797,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA: \u003c/strong\u003eThe effect of co-exposure to DEN and AFB1 on antioxidant biomarkers in rats treated with AMP and CPX. The control group details are as above. Values are means ± SD for eight rats per group. Connecting lines show comparisons; significance at (p\u0026lt;0.05); * to **** indicate significance; ns: not significant. AFB1: Aflatoxin B1; CPX: Ciprofloxacin; AMP: Ampicillin; DEN: Diethylnitrosamine; GPX: Glutathione Peroxidase; GSH: Reduced Glutathione.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB: \u003c/strong\u003eThe effect of co-exposure to DEN and AFB1 on TSH levels in rats treated with AMP and CPX. The control group details are as above. Values are means ± SD for eight rats per group. Connecting lines compare groups; significance at (p\u0026lt;0.05); * to **** indicate significance; ns: not significant. AFB1: Aflatoxin B1; CPX: Ciprofloxacin; AMP: Ampicillin; DEN: Diethylnitrosamine; TSH: Total Sulfhydryl.\u003c/p\u003e","description":"","filename":"Fig9.png","url":"https://assets-eu.researchsquare.com/files/rs-9094434/v1/323d1aba31bf0f3a82bb6aa0.png"},{"id":105509516,"identity":"12fd82e0-db58-40dc-a376-87fef4c2b7be","added_by":"auto","created_at":"2026-03-26 20:11:35","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":1729587,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of co-exposure of DEN and AFB\u003csub\u003e1\u003c/sub\u003e on pro-inflammatory biomarkers, MPO and NO in rats treated with AMP and CPX, Control, (2 mL/kg); AMP, 20mg/kg, CPX, 12.5mg/kg, DEN, 200mg/kg, AFB\u003csub\u003e1\u003c/sub\u003e, 2mg/kg; AMP+DEN (20+200)mg/kg, CPX+DEN (12.5+200)mg/kg, AMP+AFB\u003csub\u003e1\u003c/sub\u003e(20+2)mg/kg, CPX+AFB\u003csub\u003e1\u003c/sub\u003e(12.5+2)mg/kg. Values are expressed as mean ± SD for eight rats per cohort. Connecting lines indicate cohort compared to one another, and the significance level was set at (\u003cem\u003ep\u0026lt;0.05\u003c/em\u003e); * to ****: indicates the significance level; ns: not significant. AFB\u003csub\u003e1\u003c/sub\u003e, Aflatoxin B\u003csub\u003e1;\u003c/sub\u003e CPX, Ciprofloxacin; AMP, Ampicillin; DEN, Diethylnitrosamine; MPO, Myeloperoxidase; NO, Nitric oxide.\u003c/p\u003e","description":"","filename":"Fig10.png","url":"https://assets-eu.researchsquare.com/files/rs-9094434/v1/d1ca108cad0c5bbf7a0c183b.png"},{"id":105509514,"identity":"f5d1cb59-3824-4ead-88f2-1f2368959f3c","added_by":"auto","created_at":"2026-03-26 20:11:35","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":1715691,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of co-exposure of DEN and AFB\u003csub\u003e1\u003c/sub\u003e on oxidative stress biomarkers, LPO, and tumor biomarker, alpha feto-protein in rats treated with AMP and CPX, Control, (2 mL/kg); AMP, 20mg/kg, CPX, 12.5mg/kg, DEN, 200mg/kg, AFB\u003csub\u003e1\u003c/sub\u003e, 2mg/kg; AMP+DEN (20+200)mg/kg, CPX+DEN (12.5+200)mg/kg, AMP+AFB\u003csub\u003e1\u003c/sub\u003e(20+2)mg/kg, CPX+AFB\u003csub\u003e1\u003c/sub\u003e(12.5+2)mg/kg. Values are expressed as mean ± SD for eight rats per cohort. Connecting lines indicate cohort compared to one another, and the significance level was set at (\u003cem\u003ep\u0026lt;0.05\u003c/em\u003e); * to ****: indicates the significance level; ns: not significant. AFB\u003csub\u003e1\u003c/sub\u003e, Aflatoxin B\u003csub\u003e1;\u003c/sub\u003e CPX, Ciprofloxacin; AMP, Ampicillin; DEN, Diethylnitrosamine; LPO, Lipid peroxidation.\u003c/p\u003e","description":"","filename":"Fig11.png","url":"https://assets-eu.researchsquare.com/files/rs-9094434/v1/c9e8995f253f77592d33473d.png"},{"id":105509512,"identity":"a9c35872-ef6f-40f5-8a92-704f72aa2354","added_by":"auto","created_at":"2026-03-26 20:11:35","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":1441884,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA:\u003c/strong\u003e The effect of co-exposure of DEN and AFB\u003csub\u003e1\u003c/sub\u003e on anti-inflammatory cytokine, IL-10 in rats treated with AMP and CPX, Control, (2 mL/kg); AMP, 20mg/kg, CPX, 12.5mg/kg, DEN, 200mg/kg, AFB\u003csub\u003e1\u003c/sub\u003e, 2mg/kg; AMP+DEN (20+200)mg/kg, CPX+DEN (12.5+200)mg/kg, AMP+AFB\u003csub\u003e1\u003c/sub\u003e(20+2)mg/kg, CPX+AFB\u003csub\u003e1\u003c/sub\u003e(12.5+2)mg/kg. Values are expressed as mean ± SD for eight rats per cohort. Connecting lines indicate cohort compared to one another, and the significance level was set at (\u003cem\u003ep\u0026lt;0.05\u003c/em\u003e); * to ****: indicates the significance level; ns: not significant. AFB\u003csub\u003e1\u003c/sub\u003e, Aflatoxin B\u003csub\u003e1;\u003c/sub\u003e CPX, Ciprofloxacin; AMP, Ampicillin; DEN, Diethylnitrosamine, IL-10, Interleukin 10.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB:\u003c/strong\u003e The effect of co-exposure of DEN and AFB\u003csub\u003e1\u003c/sub\u003e on pro-apoptotic biomarker, Caspase 3 activity in rats treated with AMP and CPX, Control, (2 mL/kg); AMP, 20mg/kg, CPX, 12.5mg/kg, DEN, 200mg/kg, AFB\u003csub\u003e1\u003c/sub\u003e, 2mg/kg; AMP+DEN (20+200)mg/kg, CPX+DEN (12.5+200)mg/kg, AMP+AFB\u003csub\u003e1\u003c/sub\u003e(20+2)mg/kg, CPX+AFB\u003csub\u003e1\u003c/sub\u003e(12.5+2)mg/kg. Values are expressed as mean ± SD for eight rats per cohort. Connecting lines indicate cohort compared to one another, and the significance level was set at (\u003cem\u003ep\u0026lt;0.05\u003c/em\u003e); * to ****: indicates the significance level; ns: not significant. AFB\u003csub\u003e1\u003c/sub\u003e, Aflatoxin B\u003csub\u003e1;\u003c/sub\u003e CPX, Ciprofloxacin; AMP, Ampicillin; DEN, Diethylnitrosamine.\u003c/p\u003e\n\u003cp\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e\u003c/p\u003e","description":"","filename":"Fig12.png","url":"https://assets-eu.researchsquare.com/files/rs-9094434/v1/bb4f41ce8c983c3d5c25e017.png"},{"id":109204424,"identity":"8c10e39d-4a76-4f92-8cb0-8723c956abd8","added_by":"auto","created_at":"2026-05-13 14:59:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":15223936,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9094434/v1/5d5311cb-0786-45db-b4b0-957af2bdd74b.pdf"},{"id":105566954,"identity":"068bb5c1-3150-4a5a-9dae-be91fefe6112","added_by":"auto","created_at":"2026-03-27 12:57:47","extension":"doc","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":139264,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables12GutMicrobialAnalysis.doc","url":"https://assets-eu.researchsquare.com/files/rs-9094434/v1/06bb819dea6c01e02178d573.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"Gut microbial imbalances caused by unrestricted antibiotic use and exposure to chemical carcinogens contribute to liver and kidney toxicity: insights from in silico and in vivo studies","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe gut microbiome, which is mainly composed of bacteria, plays a vital role in health and disease [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Evidence has shown that over 2000 bacterial species have been identified in the human gut belonging to different phyla, including \u003cem\u003eBacteroidetes\u003c/em\u003e, \u003cem\u003eFirmicutes, Proteobacteria, Fusobacteria, Actinobacteria\u003c/em\u003e, \u003cem\u003eVerrucomicrobia\u003c/em\u003e, and \u003cem\u003eCyanobacteria\u003c/em\u003e [\u003cspan additionalcitationids=\"CR3 CR4 CR5\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The gut microbiota plays a vital role in humans by supporting gut homeostasis, protecting against pathogen invasion, enhancing immune system development, and producing signalling molecules [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Of note, the beneficial gut microbes maintain a fragile equilibrium, which, when disrupted, leads to impaired intestinal mucosal barrier function, inflammation, impaired immunity, behaviour, and metabolic function [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This forms the pathological basis of several diseases, including gut dysbiosis [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInterestingly, unrestricted use of antibiotic treatment, whether short- or long-term, negatively impacts microbiota health [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Although, reportedly used to eradicate specific pathogenic bacteria saving millions of lives [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], its non-specific action on pathogens result depletion of the normal gut microbiota community [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] including the \u003cem\u003ebifidobacteria, lactobacteria, actinobacteria\u003c/em\u003e, and \u003cem\u003eLachnospiraceae\u003c/em\u003e while, causing an increase in the opportunistic and pathogenic bacteria including \u003cem\u003eEnterobacteriaceae, Bacteroidaceae, enterococci\u003c/em\u003e, and drug-resistant \u003cem\u003eEscherichia coli\u003c/em\u003e [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. These effects are commonly associated with several prescribed antibiotic classes, including beta-lactam antibiotics, aminoglycosides, daptomycin, fluoroquinolones, glycopeptides (teicoplanin and vancomycin) and linezolid [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. While gut dysbiosis remains a potent risk factor for certain diseases, including gastrointestinal diseases, liver disease, diabetes and cancer [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Its role in carcinogen-exposed individuals (mycotoxins and Nitrosamines) remains unknown.\u003c/p\u003e \u003cp\u003eAmong well-known carcinogens are aflatoxins, a class of mycotoxins produced predominantly by \u003cem\u003eAspergillus flavus\u003c/em\u003e and \u003cem\u003eAspergillus parasiticus\u003c/em\u003e, which pose a serious health risk to both humans and animals [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Aflatoxin contamination affects approximately 25% of the global food supply and nearly 40% of food crops in sub-Saharan Africa, thereby placing a hefty burden on developing countries. [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Over 4\u0026nbsp;billion people worldwide are exposed to dietary aflatoxins, especially aflatoxin B\u003csub\u003e1\u003c/sub\u003e (AFB\u003csub\u003e1\u003c/sub\u003e), in peanuts, maize, and tree nuts, which are strongly associated with liver cancer (hepatocellular carcinoma) in humans [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. AFB\u003csub\u003e1\u003c/sub\u003e also causes multiorgan damage, especially the gut, spleen, lungs, brain, liver and kidney, immune system suppression and cancer [\u003cspan additionalcitationids=\"CR32 CR33\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] through liver cytochrome P-450 activation, producing a highly reactive metabolite known as AFB\u003csub\u003e1\u003c/sub\u003e-8,9-epoxide [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] that forms covalent DNA adduction, inducing oxidative stress, inflammation, apoptosis and epigenetic modification [\u003cspan additionalcitationids=\"CR37 CR38\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSimilarly, nitrosamines embrace a broad category of environmental carcinogens in smoked pickled fish, cheese, nitrite-cured meats, dried milk and alcoholic beverages or tobacco smoke, which presents a global concern due to its multiorgan tumorigenic effect [\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Particularly, diethyl nitrosamine (DEN) is associated with reactive oxygen species (ROS), inflammatory activation, impaired apoptosis, and overexpression of G1/S phase regulatory proteins in experimental models [\u003cspan additionalcitationids=\"CR44 CR45 CR46 CR47 CR48\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Although the carcinogenic effect of AFB\u003csub\u003e1\u003c/sub\u003e and DEN is well established, their individual effects under conditions of unrestricted antibiotic exposure remain poorly understood. Therefore, this study aims to investigate the impact of antibiotic-induced gut microbial imbalances from unrestricted use and its effects on chemical carcinogen exposure, targeting liver and kidney oxidative stress, inflammation, and apoptotic mechanisms in vivo and in silico studies.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eAcquisition of Molecular Structures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe molecular structures of CPX, AMP, AFB\u003csub\u003e1\u003c/sub\u003e, and DEN were obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov/) using its search function, which provided 2D and 3D molecular structures as well as SMILES notation [50].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNetwork Toxicology and Molecular Docking\u003c/strong\u003e\u003cbr\u003eWe constructed a ligand\u0026ndash;target network for Ampicillin (AMP), Ciprofloxacin (CPX), Aflatoxin B\u003csub\u003e1\u003c/sub\u003e (AFB\u003csub\u003e1\u003c/sub\u003e), and Diethyl nitrosamine (DEN) by combining predicted ligand targets obtained from SwissTargetPrediction (https://www.swisstargetprediction.ch/) accessed on 27th October 2025. Protein\u0026ndash;protein interactions (PPI) for the intersecting gene set were retrieved from STRING (v11) and visualised in Cytoscape (v3.9). Hub proteins were identified using CytoHubba (MCC algorithm) and prioritised for structural analysis.\u003c/p\u003e\n\u003cp\u003eThree-dimensional ligand structures were downloaded on 28th October 2025, from PubChem (https://pubchem.ncbi.nlm.nih.gov/) and converted to pdb/pdbqt using BIOVIA (v3.x). Receptor structures were obtained from the RCSB PDB (https://www.rcsb.org/) and accessed on 28th October 2025. Targets lacking were prepared by removing non-essential ligands/waters, adding polar hydrogens at pH 7.4, and converting to pdbqt with MGLTools. Initial rigid docking was performed using PyRx with search exhaustiveness = 16, num_modes = 20, and an energy_range = 4. Grid boxes were centred on co-crystallised ligands where present, or on predicted pockets (CASTp/DoGSite) where absent; box sizes were set between 18\u0026ndash;28 \u0026Aring; depending on pocket volume. Docking results were ranked by binding energy and visually inspected in Biovia Discovery Studio (2021). Docked poses were analysed for hydrogen bonds, hydrophobic contacts and interactions with catalytic residues.\u003c/p\u003e\n\u003cp\u003eDocking-derived ligand protein edge weights were integrated back into the PPI network (edge weight\u0026nbsp;\u0026prop;\u0026nbsp;\u0026minus;docking score) in Cytoscape to identify ligand-influenced hubs and enriched pathways. All scripts, parameter files and raw docking/MD outputs are available on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eToxicity analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe SMILES notations of AFB\u003csub\u003e1\u003c/sub\u003e and DEN were inserted into the \u0026ldquo;Predict compound toxicity\u0026rdquo; module of ProTox 3.0 [51] (https://tox.charite.de/protox3/) to generate toxicity profiles. Similarly, the SMILES notations were submitted to (http://admetmesh.scbdd.com/) to obtain predictions for specific toxicity endpoints[52].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChemicals, Reagents and Kits\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAflatoxin B\u003csub\u003e1\u003c/sub\u003e (1162-65-8), 5,5\u0026rsquo;-dithiobis-(2-nitrobenzoic\u0026nbsp;acid) (69-78-3), Formalin (590-46-5), Epinephrine (51-43-4), Hydrogen\u0026nbsp;peroxide (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e) (7722-84-1), O-Dianisidine (119-90-4), Reduced glutathione\u0026nbsp;(GSH) (70-18-8), Sodium-Potassium\u0026nbsp;tartrate (6381-59-5), Sodium azide, Sulfosalicylic\u0026nbsp;acid (5965-83-3), Thiobarbituric\u0026nbsp;acid\u0026nbsp;(TBA) (504-17-6), 2\u0026rsquo;,7\u0026rsquo;-dichlorodihydrofluorescin\u0026nbsp;diacetate (4091-99-0), \u0026nbsp;and 1-Chloro-2,4-dinitrobenzene\u0026nbsp;(CDNB) (97-00-7) and Diethyl nitrosamine (55-18-5) were purchased from Sigma-Aldrich\u0026nbsp;Inc.\u0026nbsp;(St Louis,\u0026nbsp;MO,\u0026nbsp;USA). Prof. A.K. Oyelere supplied Ampicillin and Ciproflaxin from Georgia Institute of Technology, USA.\u0026nbsp;Aspartate Aminotransferase (AST) (AS101), Alanine Aminotransferase (ALT) (AL146), Alkaline\u0026nbsp;phosphatase\u0026nbsp;(ALP) (AP307), Urea (UR1068), and Creatinine (CR510) were purchased from VWR, USA. Randox Laboratories,\u0026nbsp;UK. Dipotassium\u0026nbsp;hydrogen\u0026nbsp;phosphate\u0026nbsp;trihydrate (7758-11-4), Potassium\u0026nbsp;Chloride (7447-40-7), Potassium\u0026nbsp;dihydrogen\u0026nbsp;phosphate (7778-77-0) were purchased from AK\u0026nbsp;Scientific,\u0026nbsp;Union\u0026nbsp;City,\u0026nbsp;USA. MacConkey Agar, Nutrient Agar, Centrimide Agar, Mannitol Salt Agar, Eosin Methylene Blue Agar, Salmonella-Shigella Agar, and MRSA were obtained from HI-Media Laboratories, Maharashtra, India. \u0026nbsp;Protein\u0026nbsp;Carbonyl, Rat\u0026nbsp;\u0026alpha;-FP (Alpha-Fetoprotein) (E-EL-R00153), Rat\u0026nbsp;IL-10 (Interleukin 10) (E-EL-R0016), and Rat CASP3 (Caspase 3) (E-EL-R0160) were purchased from E-lab Biosciences Company (Wuhan, China).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExperimental design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNinety (90) male Albino Wistar rats weighing 200g \u0026plusmn; 20 g were sourced from the Faculty of Veterinary Medicine, University of Ibadan, Nigeria, and used for this study. The animals were housed in the Department of Biochemistry Experimental Animal House in spacious plastic cages within a well-ventilated vivarium, maintained under standard laboratory conditions with a 12h/12h light/dark cycle, with the light kept off during dark hours. No researchers entered the animal house during the dark cycle, and the rats had free access to rat feed and water. The animals were acclimatised for one week before the experiment commenced. Animal care and experimental protocols strictly adhered to the guidelines approved by the University of Ibadan Animal Care and Use Research Committee and the \u0026lsquo;Guide for the Care and Use of Laboratory Animals\u0026rsquo; published by the National Academy of Science (NAS) and the National Institute of Health. The study protocol received approval from the Care and Use Research Ethics Committee (ACUREC) at the University of Ibadan (UI-ACUREC/068-0524/06). Following the one-week acclimatisation period, the rats were randomly allocated into nine (9) cohorts, each comprising ten (10)\u0026nbsp;rats. The rats were treated with Ampicillin [53] or Ciprofloxacin [54] for two weeks, and from each group, two rats were randomly selected to provide faecal samples from the colon for microbial analysis to assess microbial population counts. On day 15, a single intraperitoneal injection of diethyl nitrosamine [55] and Aflatoxin B\u003csub\u003e1\u0026nbsp;\u003c/sub\u003e[56] was administered, while antibiotic treatment continued for an additional seven days. The animals were sacrificed on day twenty-two, as illustrated in \u003cstrong\u003eFigure 1\u003c/strong\u003e and as outlined below:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGroup 1: (Control)\u0026nbsp;\u003c/strong\u003e2 mL/Kg normal saline \u003cem\u003eper os\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGroup 2:\u003c/strong\u003e \u003cstrong\u003eAmpicillin (AMP)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e50 mg/Kg \u003cem\u003eper os\u003c/em\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGroup 3:\u0026nbsp;Ciprofloxacin (CPX)\u003c/strong\u003e 12.5 mg/Kg \u003cem\u003eper os\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eGroup 4:\u003c/strong\u003e \u003cstrong\u003eDiethylnitrosamine (DEN)\u003c/strong\u003e 200 mg/Kg \u003cem\u003ei.p\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGroup 5:\u003c/strong\u003e \u003cstrong\u003eAflatoxin B\u003csub\u003e1\u003c/sub\u003e\u003c/strong\u003e \u003cstrong\u003e(AFB\u003csub\u003e1\u003c/sub\u003e)\u0026nbsp;\u003c/strong\u003e2 mg/Kg \u003cem\u003ei.p.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGroup 6:\u003c/strong\u003e \u003cstrong\u003eAMP + DEN\u003c/strong\u003e: \u003cstrong\u003eAMP (\u003c/strong\u003e50 mg/Kg) + \u003cstrong\u003eDEN\u003c/strong\u003e (200 mg/Kg\u003cem\u003e; i.p.\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGroup 7: CPX + DEN\u003c/strong\u003e: \u003cstrong\u003eCPX\u003c/strong\u003e (12.5 mg/Kg) + \u003cstrong\u003eDEN\u003c/strong\u003e (200 mg/Kg\u003cem\u003e; i.p.\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGroup 8: AMP + AFB\u003csub\u003e1\u003c/sub\u003e\u003c/strong\u003e: \u003cstrong\u003eAMP\u003c/strong\u003e (50 mg/Kg) \u0026nbsp;+ \u003cstrong\u003eAFB\u003csub\u003e1\u0026nbsp;\u003c/sub\u003e(\u003c/strong\u003e2 mg/Kg\u003cem\u003e; i.p.\u003c/em\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGroup 9: CPX + AFB\u003csub\u003e1\u003c/sub\u003e\u003c/strong\u003e: \u003cstrong\u003eCPX\u003c/strong\u003e (12.5 mg/Kg) + \u003cstrong\u003eAFB\u003csub\u003e1\u0026nbsp;\u003c/sub\u003e(\u003c/strong\u003e2 mg/Kg\u003cem\u003e; i.p.\u003c/em\u003e).\u003c/p\u003e\n\u003cp\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample Microbial Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing acclimatisation and before treatment, two animals from each group were randomly chosen for bacterial culture and population analysis. The rats were humanely euthanised, after which colon faecal material was collected aseptically for bacterial culture. 1 g of the colon faecal sample was weighed and diluted in 9 mL of sterile water to produce a 10^-1 dilution. The mixture was vortexed, and 1 mL was transferred into 9 mL of sterile water to create a 10^-2 serial dilution. From this dilution, 0.2 mL was added to a petri dish containing freshly prepared Nutrient Agar, and the sample was gently spread over the media with a sterile glass rod to ensure even distribution.\u003c/p\u003e\n\u003cp\u003eAdditionally, 0.1 mL of the 10^-2 dilution was plated onto Eosin Methylene Blue (EMB), MacConkey, Cetrimide, Salmonella-Shigella Agar (SSA), Mannitol Salt Agar (MSA), and Methicillin-resistant Staphylococcus aureus Agar (MRSA) plates. The plates were incubated at 37\u0026deg;C for 24 hours to promote bacterial growth. Once incubation was complete, the number of bacterial colonies on each plate was counted with a colony counter. After 21 days of treatment, the bacterial culture process was repeated using the same procedure. Results were reported as colony-forming units (CFU) per mL.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstimation of Gut Microbial Population\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cimg src=\"https://myfiles.space/user_files/58895_8739fc6c57c1c19a/58895_custom_files/img1774544001.png\" width=\"839\" height=\"94\"\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTissue Sample Collection and Biochemical Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe final body weights of experimental animals were measured on day 21, 24 hours after the\u0026nbsp;last treatment, before exsanguination was performed via the retro-orbital venous plexus to\u0026nbsp;collect blood samples into labelled plain tubes. Rats were then sacrificed by dislocating their\u0026nbsp;cervical vertebrae. Whole blood was allowed to stand at room temperature for 30 minutes, and\u0026nbsp;serum was obtained by centrifugation at 3000 g for 10 minutes in a cold centrifuge at 4\u0026deg;C.\u0026nbsp;Subsequently, serum samples were preserved at -20\u0026deg;C pending routine analysis of enzymes relevant to the liver and kidney. Furthermore, the organs of interest, i.e., the liver and the kidney, were immediately removed, rinsed in ice-cold potassium chloride (KCl) solution,\u0026nbsp;weighed, and recorded, then processed\u0026nbsp;for\u0026nbsp;histological and biochemical tests. Harvested tissue samples (liver and kidney) were rinsed in ice-cold 1.15% KCl\u0026nbsp;solution, blotted\u0026nbsp;with\u0026nbsp;filter\u0026nbsp;paper,\u0026nbsp;and\u0026nbsp;weighed\u0026nbsp;to\u0026nbsp;determine\u0026nbsp;their\u0026nbsp;initial\u0026nbsp;weights. Thereafter, the liver and the kidney samples were sectioned for histological examination and immersed in\u0026nbsp;formalin.\u0026nbsp;The\u0026nbsp;remaining\u0026nbsp;portions of\u0026nbsp;the\u0026nbsp;harvested\u0026nbsp;liver\u0026nbsp;and kidney\u0026nbsp;were\u0026nbsp;homogenised\u0026nbsp;with\u0026nbsp;0.1 M\u0026nbsp;phosphate buffer (pH 7.4) using a Teflon homogeniser. The homogenates obtained were then\u0026nbsp;centrifuged\u0026nbsp;at\u0026nbsp;10,000\u0026nbsp;revolutions\u0026nbsp;per\u0026nbsp;minute\u0026nbsp;(rpm)\u0026nbsp;for\u0026nbsp;15\u0026nbsp;minutes\u0026nbsp;in\u0026nbsp;a\u0026nbsp;cold\u0026nbsp;centrifuge\u0026nbsp;(4\u0026deg;C)\u0026nbsp;to obtain the post-mitochondrial fraction. After centrifugation, the supernatants were collected\u0026nbsp;for\u0026nbsp;biochemical\u0026nbsp;and\u0026nbsp;inflammatory\u0026nbsp;analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of Liver and Kidney Function Biomarkers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe activity and the level of liver and kidney function biomarkers in the rats were assessed using the Randox\u0026trade; Laboratory analytical reagent kit. The levels of liver enzymes\u0026mdash;Alkaline Phosphatase (ALP), Aspartate Aminotransferase (AST), and Alanine Aminotransferase (ALT)\u0026mdash;Creatine and Urea were measured according to the colourimetric methods and protocols provided in the manufacturer\u0026apos;s manual, utilising a Molecular Devices Multimodal Spectrophotometer 384\u003csup\u003eTM\u003c/sup\u003e (San Jose, CA, USA). The levels of creatinine and urea in the animals\u0026apos; kidneys were also estimated according to the manufacturer\u0026apos;s instructions and guidelines. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of rats\u0026rsquo; antioxidant biomarkers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe activity of antioxidant biomarkers in the supernatant of the liver and kidney of rats was assessed. Superoxide dismutase (SOD) was measured using the Misra and Fridovich method, which involves determining SOD inhibitory activity on the auto-oxidation reaction of adrenaline; 50 \u0026micro;L of sample was added to 2.5 mL of 0.05 M carbonate buffer (pH 10.2) and 0.3 mL of epinephrine in a cuvette, mixed by inversion, with the change in absorbance recorded every 30 seconds for 2 minutes at 480 nm [57]. Glutathione-\u003cem\u003eS\u003c/em\u003e-transferase (GST) activity was estimated using the method of Habig et al. [58]. 50 \u0026micro;L of sample was added to 170 \u0026micro;L of the reaction mixture (20 mL phosphate buffer, 0.5 mL reduced glutathione, and 10.5 mL distilled water), and 10 \u0026micro;L of 20 mM 1-chloro-2,4-dinitrobenzene was added to the cuvette. The contents were gently mixed, and the change in absorbance at 340 nm was monitored every 60 seconds for 3 minutes against a reagent blank containing all components except the sample.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGlutathione peroxidase (GPx) activity was measured following the method of Rotruck et al. [59], using 50 \u0026micro;L of tissue supernatant mixed with a reaction solution containing 500 \u0026micro;L of potassium phosphate buffer (pH 7.0), 100 \u0026micro;L of NANO3, 200 \u0026micro;L of GSH (4 mM), 100 \u0026micro;L of H₂O₂ (2.5 mM), 500 \u0026micro;L of distilled water, and the sample. The mixture was incubated at 37\u0026deg;C for 3 minutes, then the reaction was stopped by adding 500 \u0026micro;L of 10% TCA and centrifuged at 3000 rpm for 5 minutes. The supernatant was then combined with K₂HPO₄ (0.3 M) and 50 \u0026micro;L of DTNB (0.04%), and absorbance was read at 412 nm after 3 minutes. Reduced glutathione (GSH) levels were estimated using the method of Beutler et al. [60]. Total thiol groups (TSH) were determined according to the method of Hu and Dillard [61], which involves reaction with dithionitrobenzoic acid (DTNB) to produce a yellow compound that absorbs at 412 nm.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of rats\u0026rsquo; pro-inflammatory, apoptotic and tumour biomarkers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePro-inflammatory biomarkers, namely Myeloperoxidase and Nitric oxide levels, were evaluated. Myeloperoxidase (MPO) activity, an indicator of polymorphonuclear leukocyte infiltration, was determined using the method described by Trush \u003cem\u003eet al.\u0026nbsp;\u003c/em\u003e[57]. MPO activity was measured spectrophotometrically with o-dianisidine (Sigma-Aldrich) and hydrogen peroxide. In the presence of H₂O₂ as an oxidising agent, MPO catalyses the oxidation of o-dianisidine, resulting in a brown-coloured oxidised product with a peak absorbance at 470 nm. The level of nitric oxide was assessed following the method of Green \u003cem\u003eet al.\u0026nbsp;\u003c/em\u003e[58]. Nitrite mediates nitrosative modification using Griess reagent\u0026mdash;mixed in a 1:1 ratio of sulfanilamide (1%) and N-naphthyl ethylenediamine dihydrochloride (0.1%)\u0026mdash;to produce a pink-orange coloured product, with absorbance measured at 550 nm. The oxidative stress biomarker lipid peroxidation (LPO) was determined by measuring the formation of thiobarbituric acid reactive substances (TBARS) in tissue homogenate, using 30% trichloroacetic acid to deproteinise the tissue, which was then mixed with 0.75% thiobarbituric acid (TBA), boiled at 80\u0026deg;C, cooled on ice, and centrifuged at 3000 rpm for 10 minutes. Supernatants were read at 532 nm using the SpectraMax\u0026trade; 384 multimodal plate reader [59]. Tissue concentrations of the tumour biomarker alpha-fetoprotein (AFP), as well as anti-inflammatory indices interleukin 10 (IL-10) and apoptosis marker caspase 3, were analysed using ELISA kits according to the manufacturer\u0026apos;s protocol. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData obtained in this study are expressed as means \u0026plusmn; SD and analysed using one-way ANOVA and Bonferroni post-hoc test (GraphPad Prism version 10.0 for MacOS, CA, USA). The level of statistical significance was set at *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001 versus AMP-, CPX-, DEN-, and AFB\u003csub\u003e1\u003c/sub\u003e-induced rats.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eNetwork Pharmacology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e179 target genes were identified for AFB\u003csub\u003e1\u003c/sub\u003e, DEN, CPX, and AMP, as shown in the Venn diagram and network graph (Fig. 3A and B). Of these, 172 are specific to CPX and AMP, as depicted in the Venn diagram and network graph (Fig. 2A). Seven intersection genes were chosen for further analysis. STAT3, EGFR, MAPK8, IKBKB, MMP2, MET, and NOS2 emerged as the hub targets based on MCC values.\u0026nbsp;The PPI network consisted of seven nodes and fifteen edges. The topological parameters of the PPI network are displayed in \u003cstrong\u003eFig. 2D, and E\u003c/strong\u003e.\u0026nbsp;Enrichment analysis results were filtered using -log\u003csub\u003e10\u003c/sub\u003e(FDR), and the top 20 GO terms selected and shown in \u003cstrong\u003eFig.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e. The results indicated that the targets of the toxicants and antibiotics are involved in biological processes such as responses to oxidative stress, inflammatory response, and regulation of cell communication. The targets are associated with cellular components (CC), such as the membrane raft, receptor complex, and basal plasma membrane. Their molecular functions (MF) include kinase activity, protein kinase binding, and carbohydrate derivative binding. The top 20 KEGG pathway enrichment terms were highlighted in \u003cstrong\u003eFig. 3B\u003c/strong\u003e, with the MAPK Signalling Pathway illustrated in Fig. 4. KEGG analysis revealed that these targets encompass EGFR tyrosine kinase inhibitor resistance, chemical carcinogenesis, reactive oxygen species, and the MAPK signalling pathway.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular Docking\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMolecular docking was performed to evaluate the binding affinities and interaction modes of Aflatoxin B\u003csub\u003e1\u003c/sub\u003e (AFB\u003csub\u003e1\u003c/sub\u003e), Ciprofloxacin (CPX), Ampicillin (AMP), and Diethylnitrosamine (DEN) with Epidermal Growth Factor Receptor (EGFR) and Signal Transducer and Activator of Transcription 3 (STAT3). The binding interactions are illustrated in \u003cstrong\u003eFigs 5A\u0026ndash;B\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eIn agreement with their docking scores, all ligands had high binding affinities for EGFR (AFB\u003csub\u003e1\u003c/sub\u003e = \u0026ndash;8.5 kcal/mol, CPX = \u0026ndash;7.8 kcal/mol, AMP = \u0026ndash;7.6 kcal/mol, DEN = \u0026ndash;4.8 kcal/mol). Within the EGFR active pocket, CPX demonstrated robust binding, forming carbon-hydrogen interactions with Met769, Leu768, and Asp831, as well as conventional hydrogen bonds with Lys721, Thr766, and Gln767 (\u003cstrong\u003eFig. 5A 1\u003c/strong\u003e). A conventional hydrogen bond with Thr766 stabilises the firmly bound AFB\u003csub\u003e1\u003c/sub\u003e (\u003cstrong\u003eFig. 5A 2\u003c/strong\u003e). DEN exhibited a relatively weak interaction, forming a single hydrogen bond with Arg812 (\u003cstrong\u003eFig. 5A 4\u003c/strong\u003e). AMP interacted with Lys721 and Cys773 by typical hydrogen bonds (\u003cstrong\u003eFig. 5A 3\u003c/strong\u003e). Based on these interactions, AMP, CPX, and AFB\u003csub\u003e1\u003c/sub\u003e may occupy catalytically significant regions of EGFR, thereby altering receptor function and downstream proliferative signalling.\u003c/p\u003e\n\u003cp\u003eBinding of the ligands to STAT3 showed the ligand docking scores (AFB\u003csub\u003e1\u003c/sub\u003e = -6.4kcal/mol, CPX = -6 kcal/mol, AMP = -5.7 kcal/mol, DEN = \u0026ndash;4kcal/mol). CPX displayed strong binding characterised by a conventional hydrogen bond with Asn359 and a carbon-hydrogen bond with Glu397 (\u003cstrong\u003eFig. 5B 1\u003c/strong\u003e). AFB\u003csub\u003e1\u003c/sub\u003e exhibited hydrogen bonding with Arg152 and additional carbon-hydrogen bonding with Asn265 (\u003cstrong\u003eFig. 5B 2\u003c/strong\u003e), while AMP formed stable hydrogen bonds with Asn359 and Glu159 (\u003cstrong\u003eFig. 5B 3\u003c/strong\u003e). In contrast, DEN failed to form any significant stabilising interactions, instead displaying a repulsive bond within the docking pocket (\u003cstrong\u003eFig. 5B 4\u003c/strong\u003e). The absence of favourable interactions between DEN and STAT3 supports its weaker binding affinity observed in docking simulations. Collectively, these results indicate that AFB\u003csub\u003e1\u003c/sub\u003e, CPX, and AMP exhibit strong and stable binding to both EGFR and STAT3, suggesting potential interference with signalling cascades regulating oxidative stress, inflammation, and cell proliferation. DEN, with its lower binding affinity and minimal stabilising interactions, may contribute to hepatocarcinogenesis through indirect or metabolic pathways rather than direct receptor engagement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular structure and toxicity prediction of AFB\u003csub\u003e1\u003c/sub\u003e and DEN\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 3D and 2D molecular structures of AFB\u003csub\u003e1\u003c/sub\u003e and DEN were retrieved from PubChem (Fig. 6a and 6b). Toxicological profiling by ProTox 3.0 revealed toxicity predictions and physicochemical features for AFB\u003csub\u003e1\u003c/sub\u003e and DEN, with AFB\u003csub\u003e1\u003c/sub\u003e exhibiting a higher acute toxicity profile (LD\u003csub\u003e50\u003c/sub\u003e = 3 mg/kg, Class 1) than DEN (LD\u003csub\u003e50\u003c/sub\u003e = 200 mg/kg, Class 3). Both compound predictions demonstrated 100% accuracy and a mean structural similarity of 100% to the reference compounds (\u003cstrong\u003eFig. 6\u003c/strong\u003e). Analysis via ADMETlab provided a comprehensive profile of 13 physicochemical properties for AFB\u003csub\u003e1\u003c/sub\u003e and DEN. This included specified upper and lower limits for properties such as molecular weight and octanol-water partition coefficient (logP), as well as compound properties (\u003cstrong\u003eFig. 6a and 6b\u003c/strong\u003e). The compounds exhibited strong carcinogenicity and mutagenicity signals (\u003cstrong\u003eTable 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGut microbial colonies were adversely affected by ampicillin and ciprofloxacin treatment and worsened by co-treatment with diethyl nitrosamine and aflatoxin B\u003csub\u003e1\u003c/sub\u003e.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePre-treatment gut microbial counts and diversity are similar to those typically found in a rodent\u0026apos;s gut. The population of Lactobacillus, which is associated with healthy gut function, was higher in control rodents than in those treated with antibiotics. Antibiotic treatment reduced beneficial Lactobacillus bacteria. This reduction was further intensified by co-treatment with AFB1 and DEN, as shown in \u003cstrong\u003eSupplementary Table 1\u003c/strong\u003e. A decline in Lactobacillus levels can lead to the overgrowth of pathogenic bacteria, disruption of the gut barrier (leaky gut), altered metabolism, and increased inflammation, potentially resulting in various diseases. Refer to \u003cstrong\u003eSupplementary Table 2\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiethylnitrosamine and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eaflatoxin B\u003csub\u003e1\u003c/sub\u003e resulted in reduced body weight and lower organ-to-body weight indices in rats co-administered with ampicillin and ciprofloxacin.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs depicted in \u003cstrong\u003eTable 2\u003c/strong\u003e, there was a significant increase in body weight and in organ-to-body weight ratio somatic indices of rats across the groups following 21-day repeated exposure to antibiotics (AMP, CPX) and co-exposure to single doses of DEN and AFB\u003csub\u003e1\u003c/sub\u003e.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eCompared with control, treatment with AMP, CPX, and AMP + DEN showed a significant decrease in final body weight, with a marked reduction in weight gain across all groups; the effect was most pronounced in AMP + DEN, CPX + DEN, and CPX + AFB\u003csub\u003e1\u003c/sub\u003e. Liver weight in groups treated with DEN, CPX + DEN, CPX + AFB1, AMP + DEN, CPX + DEN, AMP + AFB1, and CPX + AFB\u003csub\u003e1\u003c/sub\u003e was significantly increased, while CPX, AFB\u003csub\u003e1\u003c/sub\u003e, AMP + DEN, CPX + DEN, AMP + AFB\u003csub\u003e1\u003c/sub\u003e and CPX + AFB\u003csub\u003e1\u003c/sub\u003e showed a significant increase in kidney weight when compared with control. Interestingly, all treated groups demonstrated significant increase in both liver and kidney relative weight when compared with the control\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Body weight change and organosomatic of rats treated with AMP, CPX for 21 days and a single intraperitoneal dose of DEN and AFB\u003csub\u003e1\u003c/sub\u003e on day 15\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 208px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003eAMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003eCPX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 116px;\"\u003e\n \u003cp\u003eDEN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003eAFB\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003eAMP + DEN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003eCPX + DEN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003eAMP + AFB\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003eCPX + AFB\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 208px;\"\u003e\n \u003cp\u003eInitial body weight (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e204.2\u0026plusmn;9.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e192.2\u0026plusmn;5.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e196.3\u0026plusmn;8.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 116px;\"\u003e\n \u003cp\u003e211.7\u0026plusmn;8.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e217\u0026plusmn;8.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e216.8\u0026plusmn;6.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003e215\u0026plusmn;8.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e211.2\u0026plusmn;6.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003e220\u0026plusmn;10.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 208px;\"\u003e\n \u003cp\u003eFinal body weight (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e234.7\u0026plusmn;12.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e206.2\u0026plusmn;10.25*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e197.7\u0026plusmn;8.21***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 116px;\"\u003e\n \u003cp\u003e208.8\u0026plusmn;15.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e217.7\u0026plusmn;11.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e205.7\u0026plusmn;20.36*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003e210.2\u0026plusmn;12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e216.8\u0026plusmn;7.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003e211.3\u0026plusmn;15.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 208px;\"\u003e\n \u003cp\u003eWeight gain (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e30.5\u0026plusmn;17.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e14.0\u0026plusmn;11.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e1.3\u0026plusmn;6.38**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 116px;\"\u003e\n \u003cp\u003e-2.8\u0026plusmn;8.32***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.7\u0026plusmn;7.31**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e-11.2\u0026plusmn;16.77****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003e-4.8\u0026plusmn;8.57***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e5.7\u0026plusmn;8.91*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003e-8.7\u0026plusmn;16.65****\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 208px;\"\u003e\n \u003cp\u003eliver weight (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e4.7\u0026plusmn;0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e5.3\u0026plusmn;0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e5.5\u0026plusmn;0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 116px;\"\u003e\n \u003cp\u003e5.6\u0026plusmn;0.13*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e5.4\u0026plusmn;0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e5.3\u0026plusmn;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003e6.2\u0026plusmn;0.09****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e5.4\u0026plusmn;0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003e5.6\u0026plusmn;0.48*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 208px;\"\u003e\n \u003cp\u003eKidney weight (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.1\u0026plusmn;0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e1.4\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e1.5\u0026plusmn;0.09**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 116px;\"\u003e\n \u003cp\u003e1.3\u0026plusmn;0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e1.5\u0026plusmn;0.12**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1.5\u0026plusmn;0.11*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003e1.5\u0026plusmn;0.22**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e1.5\u0026plusmn;0.06**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003e1.5\u0026plusmn;0.14**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 208px;\"\u003e\n \u003cp\u003eRelative liver weight (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e2.0\u0026plusmn;0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e2.6\u0026plusmn;0.20*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e2.8\u0026plusmn;0.13****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 116px;\"\u003e\n \u003cp\u003e2.7\u0026plusmn;0.21***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e2.5\u0026plusmn;0.27*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2.6\u0026plusmn;0.28**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003e2.9\u0026plusmn;0.19****\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e2.5\u0026plusmn;0.14*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003e2.7\u0026plusmn;0.33***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 208px;\"\u003e\n \u003cp\u003eRelative kidney weight (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.5\u0026plusmn;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 103px;\"\u003e\n \u003cp\u003e0.7\u0026plusmn;0.04*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e0.8\u0026plusmn;0.03***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 116px;\"\u003e\n \u003cp\u003e0.6\u0026plusmn;0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.7\u0026plusmn;0.08**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e0.7\u0026plusmn;0.11***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 122px;\"\u003e\n \u003cp\u003e0.7\u0026plusmn;0.13***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e0.7\u0026plusmn;0.05**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 130px;\"\u003e\n \u003cp\u003e0.7\u0026plusmn;0.07**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eControl (Normal Saline 2 mL/kg, n=6), AMP (20 mg/kg, n=6), CPX (12.5 mg/kg, n=6), DEN (200 mg/kg, n=6), AMP + DEN (20 mg/kg + 200 mg/kg, n=6), CPX + DEN (12.5 mg/kg + 200 mg/kg, n=6),\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAMP + AFB\u003csub\u003e1\u003c/sub\u003e (20 mg/kg + 2 mg/kg, n=6), CPX + AFB\u003csub\u003e1\u003c/sub\u003e (12.5 mg/kg + 2 mg/kg, n=6). Values are expressed as mean \u0026plusmn; SD. * indicates values that differ significantly (p \u0026lt; 0.05) from the control. AMP, Ampicillin.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCPX, Ciprofloxacin; DEN, Diethylnitrosamine; AFB\u003csub\u003e1\u003c/sub\u003e, Aflatoxin B\u003csub\u003e1\u003c/sub\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe impact of diethylnitrosamine and aflatoxin B\u003csub\u003e1\u003c/sub\u003e on serum hepatic and renal function activities in rats co-treated with ampicillin and ciprofloxacin\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe effect of DEN and AFB\u003csub\u003e1\u003c/sub\u003e on the serum hepatic and renal function of rats cotreated with AMP and CPX is shown in \u003cstrong\u003eFig 7\u003c/strong\u003e. Compared with the control, there is an increase (p \u0026lt; 0.05) in the activities of ALP, AST, and ALT in rats treated with 20 mg/Kg AMP and 12.5 mg/Kg CPX (\u003cstrong\u003eFig. 7)\u003c/strong\u003e. Compared with the DEN and AFB\u003csub\u003e1\u003c/sub\u003e groups, there is an increase \u003cem\u003e(p\u0026lt;0.05\u003c/em\u003e) in hepatic transaminases activities\u0026mdash;ALP, AST, and ALT\u0026mdash;in rats cotreated with 20 mg/Kg AMP + 200 mg/Kg DEN, 12.5 mg/Kg CPX + 200 mg/Kg DEN, 20 mg/Kg AMP + 2 mg/Kg AFB\u003csub\u003e1,\u0026nbsp;\u003c/sub\u003eand 12.5 mg/Kg CPX + 2 mg/Kg AFB\u003csub\u003e1\u003c/sub\u003e. Compared with the control, serum urea and creatinine levels are increased (p \u0026lt; 0.05) in rats treated with 20 mg/Kg AMP and 12.5 mg/Kg CPX (\u003cstrong\u003eFig. 7)\u003c/strong\u003e. Additionally, compared to the DEN and AFB\u003csub\u003e1\u003c/sub\u003e groups, serum urea and creatinine levels are elevated (p\u0026lt;0.05) in rats cotreated with 20 mg/Kg AMP + 200 mg/Kg DEN, 12.5 mg/Kg CPX + 200 mg/Kg DEN, 20 mg/Kg AMP + 2 mg/Kg AFB\u003csub\u003e1\u003c/sub\u003e, and 12.5 mg/Kg CPX + 2 mg/Kg AFB\u003csub\u003e1\u003c/sub\u003e. This result indicates kidney damage.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe impact of diethylnitrosamine and aflatoxin B\u003csub\u003e1\u003c/sub\u003e on enzymatic antioxidant biomarkers in rats co-treated with Ampicillin and Ciprofloxacin.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe effect of DEN and AFB\u003csub\u003e1\u003c/sub\u003e on the activities of antioxidant enzymes: Superoxide Dismutase (SOD), Glutathione-\u003cem\u003es\u003c/em\u003e-transferase (GST), Glutathione Peroxidase (GPX) and Reduced Glutathione (GSH), Total Sulfhydryl (TSH) in rats cotreated with AMP and CPX is shown in \u003cstrong\u003eFig 8-9\u003c/strong\u003e. Compared with the control, the antibiotics-only treatment (20 mg/Kg AMP and 12.5 mg/Kg CPX) significantly reduced the levels of liver and kidney antioxidant biomarkers (SOD, GST, GPX, GSH, and TSH). Meanwhile, there was a greater decrease (\u003cem\u003ep\u0026lt;0.05\u003c/em\u003e) in the activities of SOD and GST (Fig 8), GPX, GSH, and TSH (Fig 8) in experimental rats co-treated with antibiotic and carcinogen cotreated groups (20 mg/Kg AMP + 200 mg/Kg DEN, 12.5 mg/Kg CPX + 200 mg/Kg DEN, 20 mg/Kg AMP + 2 mg/Kg AFB\u003csub\u003e1\u003c/sub\u003e, 12.5 mg/Kg CPX + 2mg/Kg AFB\u003csub\u003e1\u003c/sub\u003e) compared with the control groups\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe impact of diethylnitrosamine and aflatoxin B\u003csub\u003e1\u003c/sub\u003e on oxidative stress and pro-inflammatory biomarkers in rats co-treated with ampicillin and ciprofloxacin\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe effect of DEN and AFB\u003csub\u003e1\u003c/sub\u003e on pro-inflammatory biomarkers: Lipid Peroxidation (LPO) level, Myeloperoxidase (MPO) activity, and Nitric Oxide (NO) level in rats treated with AMP and CPX is illustrated in \u003cstrong\u003eFig 10 and Fig 11A\u003c/strong\u003e. Antibiotic-only treatment (20 mg/Kg AMP and 12.5 mg/Kg CPX) elevated MPO, NO (\u003cstrong\u003eFig. 9\u003c/strong\u003e), and LPO (\u003cstrong\u003eFig. 10A\u003c/strong\u003e) levels in the liver and kidneys compared with control groups. Likewise, rats cotreated with these carcinogens exhibited a greater increase (\u003cem\u003ep\u0026lt;0.05\u003c/em\u003e) in the levels of MPO, NO, and LPO (20 mg/Kg AMP + 200 mg/Kg DEN, 12.5 mg/Kg CPX + 200 mg/Kg DEN, 20 mg/Kg AMP + 2 mg/Kg AFB\u003csub\u003e1\u003c/sub\u003e, 12.5 mg/Kg CPX + 2 mg/Kg AFB\u003csub\u003e1\u003c/sub\u003e) when compared with controls.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe impact of diethylnitrosamine and aflatoxin B\u003csub\u003e1\u003c/sub\u003e on anti-inflammatory cytokines in rats co-treated with ampicillin and ciprofloxacin\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe effect of DEN and AFB\u003csub\u003e1\u003c/sub\u003e on liver and kidney anti-inflammatory cytokine: Interleukin 10 (IL-10) levels in rats treated with AMP and CPX is shown in \u003cstrong\u003eFig 12.\u003c/strong\u003e Compared with the untreated control, there is a decrease (\u003cem\u003ep\u0026lt;0.05\u003c/em\u003e) in IL-10 levels in the treated control groups: 20 mg/Kg AMP, 12.5 mg/Kg CPX, 200 mg/Kg DEN, 2 mg/Kg AFB\u003csub\u003e1,\u0026nbsp;\u003c/sub\u003eand in the co-treated groups: 20 mg/Kg AMP + 200 mg/Kg DEN, 12.5 mg/Kg CPX + 200 mg/Kg DEN, 20 mg/Kg AMP + 2 mg/Kg AFB\u003csub\u003e1\u003c/sub\u003e, 12.5 mg/Kg CPX + 2 mg/Kg AFB\u003csub\u003e1\u003c/sub\u003e. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe impact of diethylnitrosamine and aflatoxin B\u003csub\u003e1\u003c/sub\u003e on tumour biomarkers in rats co-treated with ampicillin and ciprofloxacin\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe effect of DEN and AFB\u003csub\u003e1\u003c/sub\u003e on the liver and kidney tumour biomarker alpha-fetoprotein (\u0026alpha;-FP) levels in rats co-treated with AMP and CPX is shown in \u003cstrong\u003eFig. 11B.\u003c/strong\u003e Compared with the untreated control, there is an increase (\u003cem\u003ep\u0026lt;0.05\u003c/em\u003e) in the level of \u0026alpha;-FP in the antibiotics-only groups (20 mg/Kg AMP, 12.5 mg/Kg CPX, 200 mg/Kg), carcinogen-treated groups (DEN, 2 mg/Kg AFB\u003csub\u003e1\u003c/sub\u003e), and the co-treated cohorts: 20 mg/Kg AMP + 200 mg/Kg DEN, 12.5 mg/Kg CPX + 200 mg/Kg DEN, 20 mg/Kg AMP + 2 mg/Kg AFB\u003csub\u003e1\u003c/sub\u003e, 12.5 mg/Kg CPX + 2 mg/Kg AFB\u003csub\u003e1\u003c/sub\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe effect of diethylnitrosamine and aflatoxin B\u003csub\u003e1\u003c/sub\u003e on pro-apoptotic biomarkers in rats co-treated with ampicillin and ciprofloxacin.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe effect of DEN and AFB\u003csub\u003e1\u003c/sub\u003e on liver and kidney pro-apoptotic biomarkers, specifically caspase 3 activity in rats treated with AMP and CPX, as well as in co-treated experimental rats, is shown in \u003cstrong\u003eFig 12B.\u003c/strong\u003e Compared to the untreated control, there is an increase (\u003cem\u003ep\u0026lt;0.05\u003c/em\u003e) in Caspase 3 activity in the treated control groups: 20 mg/Kg AMP, 12.5 mg/Kg CPX, 200 mg/Kg DEN, 2 mg/Kg AFB\u003csub\u003e1,\u0026nbsp;\u003c/sub\u003eand in the co-treated groups: 20 mg/Kg AMP + 200 mg/Kg DEN, 12.5 mg/Kg CPX + 200 mg/Kg DEN, 20 mg/Kg AMP + 2 mg/Kg AFB\u003csub\u003e1\u003c/sub\u003e, 12.5 mg/Kg CPX + 2 mg/Kg AFB\u003csub\u003e1\u003c/sub\u003e. \u0026nbsp;\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAntibiotics are major disruptors of gut microbiota. Oral antibiotics can alter the gut microbiota by disrupting interactions between the normal gut microbiota and opportunistic and pathogenic bacteria, thereby causing dysbiosis e. Shi \u003cem\u003eet al.\u003c/em\u003e examined 16S rRNA gene sequences to assess the effects of ampicillin on colonic microbiota diversity, showing a significant reduction in total microbial numbers [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Common carcinogens, including Aflatoxin (AFB\u003csub\u003e1\u003c/sub\u003e) [\u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] and Diethylnitrosamine (DEN) [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e], have been identified as potent risk factors for human hepatocarcinogenesis.\u003c/p\u003e \u003cp\u003eMolecular docking and network toxicology were used to investigate how commonly misused antibiotics (ciprofloxacin, ampicillin) and dietary hepatocarcinogens (AFB\u003csub\u003e1\u003c/sub\u003e, DEN) influence inflammatory and pro-tumour signalling networks in the liver. Network analysis of shared targets identified a pro-inflammatory/pro-tumorigenic module (IKBKB, NOS2, MAPK8, STAT3), along with growth-promoting receptors (EGFR, MET) and the matrix remodeller MMP2. This indicates that antibiotic- induced gut dysbiosis may sensitise the liver to AFB \u003csub\u003e1\u003c/sub\u003e/DEN- induced genotoxicity [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e] by activating NF- κB/IKKβ signalling and iNOS- mediated nitrosative stress [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e], initiating JNK (MAPK 8) stress responses, and engaging EGFR/MET- STAT 3 survival pathways that support the proliferation of damaged hepatocytes [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Additionally, the relatively high docking affinities of AFB \u003csub\u003e1\u003c/sub\u003e (\u0026ndash;8.8 kcal/mol), CPX (\u0026ndash;7.8 kcal/mol), and AMP (\u0026ndash;7.7.6 kcal/mol) toward EGFR imply potential synergistic effects in modulating EGFR-mediated signalling pathways. These interactions might increase hepatocyte susceptibility to inflammation and neoplastic transformation following antibiotic- induced dysbiosis. The \u003cb\u003eweak binding of DEN (\u0026ndash;4.4 kcal/mol)\u003c/b\u003e to both EGFR and STAT3 suggests its toxicity depends less on direct receptor engagement and more on metabolic activation via cytochrome P450 enzymes (e.g., CYP2E1), as supported by the literature [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Notably, antibiotics may indirectly worsen DEN toxicity by disrupting gut microbial balance, reducing microbial metabolites such as short-chain fatty acids (SCFAs), which normally protect hepatic health, and promoting inflammatory responses through \u003cb\u003eNOS2-\u003c/b\u003emediated nitrosative stress. Moreover, network enrichment identified \u003cb\u003eMMP-2\u003c/b\u003e and \u003cb\u003eMET\u003c/b\u003e, both of which are linked to extracellular matrix degradation and oncogenic transformation, suggesting that chronic exposure to antibiotics and toxins may accelerate hepatic fibrosis and tumour progression. Complementing these network interactions, \u003cem\u003ein silico\u003c/em\u003e ADMET profiling using ProTox-3.0 and ADMETlab [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] further elucidated the toxicological profiles of AFB\u003csub\u003e1\u003c/sub\u003e and DEN (Table\u0026nbsp;3, Figs.\u0026nbsp;13 and 14). Predictive modelling revealed distinct acute oral toxicity classes (Class 1 for AFB \u003csub\u003e1\u003c/sub\u003e with a predicted LD \u003csub\u003e50\u003c/sub\u003e of 3 mg/kg; Class 3 for DEN with a predicted LD \u003csub\u003e50\u003c/sub\u003e of 200 mg/kg), along with high probabilities for carcinogenicity (AFB \u003csub\u003e1\u003c/sub\u003e: 0. 68; DEN: 0. 99) and mutagenicity (AFB \u003csub\u003e1\u003c/sub\u003e: 0. 95; DEN: 0. 96) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan additionalcitationids=\"CR71\" citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Their physicochemical properties, especially lipophilicity (logP\u0026thinsp;=\u0026thinsp;2. 28 for AFB \u003csub\u003e1\u003c/sub\u003e and 1. 01 for DEN) and molecular weights (312. 27 Da and 102.14. 14 Da, respectively), suggest favourable intestinal absorption and systemic distribution, providing a computational basis for the observed multi- organ (hepatorenal) damage and increased carcinogenesis risk \u003cem\u003ein vivo\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003eIn vivo\u003c/em\u003e experimental validation further supports a mechanistic link between microbial disruption and increased hepatocarcinogenesis in animals exposed to antibiotics and carcinogens, suggesting a potential rise in inflammatory and nitrosative stress genes. Findings showed reduced total colonic bacterial populations following pre-treatment with ampicillin (AMP) or ciprofloxacin (CPX) alone in experimental rats, as well as in groups co-treated with carcinogens (DEN and AFB\u003csub\u003e1\u003c/sub\u003e). Although specific colonic microbiota diversity was not identified, these findings corroborate earlier studies indicating antibiotic-induced gut dysbiosis [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. The results also indicated decreased body weights in the co-treated rats, with no change in organ-to-body weight ratios. This suggests potential toxicological effects on the liver and kidney, as alterations in organ weights are commonly used to assess chemically induced organ injury and toxicity [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. Liver injury markers, including hepatic transaminase activities (ALP, AST, and ALT), were elevated in all groups individually or co-exposed to antibiotics and carcinogens (DEN and AFB\u003csub\u003e1\u003c/sub\u003e) compared to controls, indicating more pronounced hepatic damage in the co-treated groups. Similar effects were observed in kidney function biomarkers (urea and creatinine), implying oxidative injury to kidney cells, especially in co-treated groups. Our findings align with earlier reports showing significantly higher levels of these markers following individual exposure to AMP, CPX, DEN, and AFB\u003csub\u003e1\u003c/sub\u003e, with aggravated hepatic and renal injuries likely due to the effects of AMP and CPX treatments [\u003cspan additionalcitationids=\"CR77 CR78 CR79\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Oxidative damage to tissues is linked to an imbalance between pro-oxidants and antioxidants [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. In this study, rats pre-treated with ampicillin and ciprofloxacin exhibited reduced hepatic and renal activities of SOD, GSH, GPx, GST, and TSH (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These effects were more pronounced in co-treated groups than in groups exposed to DEN or AFB\u003csub\u003e1\u003c/sub\u003e alone. These enzymatic and non-enzymatic antioxidants play key roles in neutralising free radicals; their reduction indicates impaired antioxidant defences and an accumulation of free radicals, which can cause potential damage to DNA, proteins, and carbohydrates, disrupting cellular functions [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. Oxidative damage to DNA is indicated by increased membrane lipid peroxidation levels in tissues [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e]. Findings showed elevated levels of lipid peroxides and nitric oxide (NO) in the livers and kidneys of rats co-treated with DEN and AFB\u003csub\u003e1\u003c/sub\u003e compared to controls, indicating that free radical generation exceeded the capacity of antioxidant enzymes to detoxify. Studies suggest that NO levels are a key factor in inflammation and nitrosative stress mediated through superoxide anion, which can disrupt the structure of macromolecules such as proteins, thereby impairing their functions [\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. The increased hepatic and renal NO levels correlated with higher myeloperoxidase (MPO) activity, an indicator of macrophage and neutrophil infiltration [\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e], which plays a crucial role in immune responses [\u003cspan additionalcitationids=\"CR89\" citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e]. MPO has been reported to catalyse the formation of reactive oxygen and nitrogen species in the presence of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e]. Our findings suggest activation of hepatic and renal inflammatory signalling following co-treatment with antibiotics and carcinogens (DEN and AFB\u003csub\u003e1),\u003c/sub\u003e alongside a suppression of anti-inflammatory cytokines such as IL-10.\u003c/p\u003e \u003cp\u003eFurthermore, the present study revealed a significant increase in caspase-3 activity in the liver and kidneys of rats co-treated with DEN and AFB\u003csub\u003e1,\u003c/sub\u003e indicating that excessive cell death [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e]. This finding supports the elevated alpha-fetoprotein (AFP) levels observed across all treated groups, which were more pronounced in the co-treated rats, indicating early severity of tissue damage and a tumourigenic event [\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e]. Although specific markers of tumourigenic signalling, including angiogenesis, metabolic reprogramming, immune evasion, and genetic and epigenetic alterations, were not assessed. Findings from this study suggest that antibiotic and carcinogen co-exposure may exacerbate tumourigenesis signalling mechanisms. These observations provide a rationale for future studies to further elucidate the molecular pathways underlying antibiotic-carcinogen interactions in cancer development. Antibiotic administration, such as AMP and CPX, decreased gut bacterial populations, thereby worsening carcinogen (DEN and AFB1)- induced hepatorenal damage by impairing hepatic and renal function, reducing antioxidant defence mechanisms, increasing oxidative stress and inflammation, and promoting excessive apoptosis and tumourigenic signalling pathways. These findings highlight the potentiating effect of combined exposure to ampicillin and ciprofloxacin on hepatorenal toxicity caused by diethylnitrosamine and aflatoxin B\u003csub\u003e1\u003c/sub\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Animal Care and Use Research Ethics Committee of the University of Ibadan (UI-ACUREC) under approval number UI-ACUREC/068-0524/06. All procedures were conducted in compliance with applicable guidelines and regulations, and in accordance with the ARRIVE guidelines (https://www.arriveguidelines.org) for reporting animal research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was conducted without a specific grant or financial support from any public, commercial, or non-profit funding agency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCredit authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSO, AKO, JC and DAB:\u003c/strong\u003e Conceptualisation, Methodology, Supervision. \u003cstrong\u003eDAB, JC, VOE, OMO, and EMP\u003c/strong\u003e: Project administration, Methodology, and investigation\u003cstrong\u003e. DAB, JC, VOE, JOB, OMO, SO, AKO and EMP\u003c/strong\u003e: Data curation, Formal analysis, Writing \u0026ndash; original draft, Writing \u0026ndash; review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no known financial conflicts of interest or personal relationships that could have influenced the work presented in this paper.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data generated in the current study are available from the corresponding author upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUse of Generative AI\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGrammarly and Microsoft Co-Pilot were used for language editing, along with the Gemini Pro version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSasso, J.M., et al., \u003cem\u003eGut Microbiome-Brain Alliance: A Landscape View into Mental and Gastrointestinal Health and Disorders.\u003c/em\u003e ACS Chem Neurosci, 2023. \u003cstrong\u003e14\u003c/strong\u003e(10): p. 1717\u0026ndash;1763.\u003c/li\u003e\n\u003cli\u003eArora, T., S. 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Frei, \u003cem\u003eOxidation of LDL by myeloperoxidase and reactive nitrogen species: reaction pathways and antioxidant protection.\u003c/em\u003e Arterioscler Thromb Vasc Biol, 2000. \u003cstrong\u003e20\u003c/strong\u003e(7): p. 1716\u0026ndash;23.\u003c/li\u003e\n\u003cli\u003eValko, M., et al., \u003cem\u003eFree radicals, metals and antioxidants in oxidative stress-induced cancer.\u003c/em\u003e Chem Biol Interact, 2006. \u003cstrong\u003e160\u003c/strong\u003e(1): p. 1\u0026ndash;40.\u003c/li\u003e\n\u003cli\u003eKlebanoff, S.J., et al., \u003cem\u003eMyeloperoxidase: a front-line defender against phagocytosed microorganisms.\u003c/em\u003e J Leukoc Biol, 2013. \u003cstrong\u003e93\u003c/strong\u003e(2): p. 185\u0026ndash;98.\u003c/li\u003e\n\u003cli\u003eNauseef, W.M., \u003cem\u003eMyeloperoxidase in human neutrophil host defence.\u003c/em\u003e Cell Microbiol, 2014. \u003cstrong\u003e16\u003c/strong\u003e(8): p. 1146\u0026ndash;55.\u003c/li\u003e\n\u003cli\u003eArnhold, J., \u003cem\u003eThe Dual Role of Myeloperoxidase in Immune Response.\u003c/em\u003e International Journal of Molecular Sciences, 2020. \u003cstrong\u003e21\u003c/strong\u003e(21): p. 8057.\u003c/li\u003e\n\u003cli\u003ePattison, D.I., M.J. Davies, and C.L. Hawkins, \u003cem\u003eReactions and reactivity of myeloperoxidase-derived oxidants: differential biological effects of hypochlorous and hypothiocyanous acids.\u003c/em\u003e Free Radic Res, 2012. \u003cstrong\u003e46\u003c/strong\u003e(8): p. 975\u0026ndash;95.\u003c/li\u003e\n\u003cli\u003eRayner, B.S., D.T. Love, and C.L. Hawkins, \u003cem\u003eComparative reactivity of myeloperoxidase-derived oxidants with mammalian cells.\u003c/em\u003e Free Radic Biol Med, 2014. \u003cstrong\u003e71\u003c/strong\u003e: p. 240\u0026ndash;255.\u003c/li\u003e\n\u003cli\u003eGrayfer, L., et al., \u003cem\u003eCharacterization and functional analysis of goldfish (Carassius auratus L.) interleukin-10.\u003c/em\u003e Mol Immunol, 2011. \u003cstrong\u003e48\u003c/strong\u003e(4): p. 563\u0026ndash;71.\u003c/li\u003e\n\u003cli\u003eFesik, S.W. and Y. Shi, \u003cem\u003eStructural biology. Controlling the caspases.\u003c/em\u003e Science, 2001. \u003cstrong\u003e294\u003c/strong\u003e(5546): p. 1477\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eKim, H., M. Jang, and E. Kim, \u003cem\u003eExploring the Multifunctional Role of Alpha-Fetoprotein in Cancer Progression: Implications for Targeted Therapy in Hepatocellular Carcinoma and Beyond.\u003c/em\u003e Int J Mol Sci, 2025. \u003cstrong\u003e26\u003c/strong\u003e(10).\u003c/li\u003e\n\u003cli\u003eWang, S., et al., \u003cem\u003eAlpha-fetoprotein acts as a novel signal molecule and mediates transcription of Fn14 in human hepatocellular carcinoma.\u003c/em\u003e J Hepatol, 2012. \u003cstrong\u003e57\u003c/strong\u003e(2): p. 322\u0026ndash;9.\u003csub\u003e\u003cbr clear=\"all\"\u003e \u003c/sub\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 and 3 are not available in this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Gut microbiota, dysbiosis, ampicillin, ciprofloxacin, diethylnitrosamine, aflatoxin B1, hepatotoxicity","lastPublishedDoi":"10.21203/rs.3.rs-9094434/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9094434/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe gut microbiota is a complex community of microorganisms that play a vital role in human health; however, antibiotic administration can disturb this balance. Such disturbances have been linked to an increased risk of various diseases, including cancer. Notably, contamination of food with Aflatoxin B \u003csub\u003e1\u003c/sub\u003e (AFB \u003csub\u003e1\u003c/sub\u003e) and Diethyl nitrosamine (DEN) has been shown to significantly raise the risk of liver cancer, as both agents are potent hepatocarcinogens associated with high incidences of hepatocellular carcinoma. This study examines the impact of widespread access to ampicillin (AMP) and ciprofloxacin (CPX)\u0026mdash;two commonly used antibiotics in Nigeria\u0026mdash;on the composition of the gut microbiota, dietary exposure to AFB\u003csub\u003e1\u003c/sub\u003e and DEN, and subsequent liver and kidney toxicity in rats. Using network toxicology, this research also explores how CPX and AMP influence gut bacteria and how AFB\u003csub\u003e1\u003c/sub\u003e and DEN trigger hepatorenal toxicity through redox and protective pathways. The study compares computational predictions with laboratory findings, identifying STAT3, EGFR, MAPK8, IKBKB, MMP2, MET, and NOS2 as key genes involved in these processes. Molecular docking results indicate that AFB \u003csub\u003e1\u003c/sub\u003e, CPX, and AMP each bind strongly to EGFR (with affinities of \u0026minus;\u0026thinsp;8. 5, \u0026minus;\u0026thinsp;7. 7.8, and \u0026minus;\u0026thinsp;7. 7.6 kcal/mol, respectively), suggesting a potential combined effect on EGFR signalling. These interactions may provide insight into how changes in the gut microbiota contribute to toxicity involving both STAT3 and EGFR. \u003cem\u003eIn vivo\u003c/em\u003e validation was carried out using male Wistar rats (n\u0026thinsp;=\u0026thinsp;90, 200g\u0026thinsp;\u0026plusmn;\u0026thinsp;20), divided into nine groups: \u003cb\u003eGroup 1\u003c/b\u003e\u0026mdash;control (2 mL saline, \u003cem\u003eper os\u003c/em\u003e); \u003cb\u003eGroup 2\u003c/b\u003e\u0026mdash;AMP (20 mg/kg, \u003cem\u003eper os\u003c/em\u003e); \u003cb\u003eGroup 3\u003c/b\u003e\u0026mdash;CPX (12. 5 mg/kg, \u003cem\u003eper os\u003c/em\u003e); \u003cb\u003eGroup 4\u003c/b\u003e\u0026mdash;DEN (200 mg/kg, \u003cem\u003ei. p.\u003c/em\u003e); \u003cb\u003eGroup 5\u003c/b\u003e\u0026mdash;AFB \u003csub\u003e1\u003c/sub\u003e (2 mg/kg); \u003cb\u003eGroup 6\u003c/b\u003e\u0026mdash;AMP\u0026thinsp;+\u0026thinsp;DEN; \u003cb\u003eGroup 7\u003c/b\u003e\u0026mdash;CPX\u0026thinsp;+\u0026thinsp;DEN; \u003cb\u003eGroup 8\u003c/b\u003e\u0026mdash;AMP\u0026thinsp;+\u0026thinsp;AFB \u003csub\u003e1\u003c/sub\u003e; \u003cb\u003eGroup 9\u003c/b\u003e\u0026mdash;CPX\u0026thinsp;+\u0026thinsp;AFB \u003csub\u003e1\u003c/sub\u003e. Two rats from each group were sampled before and after treatment to assess gut microbiota. The findings revealed that DEN, AFB \u003csub\u003e1\u003c/sub\u003e, and combinations with AMP or CPX reduced body, liver, and kidney weights (\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0. 05\u003c/em\u003e). Co- treatments elevated serum transaminase, creatinine, and urea levels, while antioxidant enzyme activity, GSH, and TSH decreased (\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0. 05\u003c/em\u003e). Markers of inflammation, lipid peroxidation, alpha- fetoprotein, and caspase- 3 increased, whereas IL- 10 decreased in the liver and kidney (\u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0. 05\u003c/em\u003e). Overall, AMP and CPX exacerbated gut dysbiosis and worsened hepatorenal toxicity with AFB \u003csub\u003e1\u003c/sub\u003e and DEN, heightening the risk of carcinogenesis.\u003c/p\u003e","manuscriptTitle":"Gut microbial imbalances caused by unrestricted antibiotic use and exposure to chemical carcinogens contribute to liver and kidney toxicity: insights from in silico and in vivo studies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-26 20:11:30","doi":"10.21203/rs.3.rs-9094434/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6f236034-5213-4e56-9c49-ac9f55fdcaa2","owner":[],"postedDate":"March 26th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-12T10:12:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-29T14:37:16+00:00","index":16,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-12T10:57:27+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-26 20:11:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9094434","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9094434","identity":"rs-9094434","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}