Establishment of Common Animal Disease Models and Their Experimental Methods
Establishment of Common Animal Disease Models and Their Experimental Methods
Animal disease models are used to reproduce key pathological events under controlled conditions, enabling standardized induction and validation of phenotypes such as elevated blood pressure, tumor initiation and progression, organ toxic injury, neurocircuit degeneration, metabolic homeostasis disruption, and immune–inflammatory cascades. Different inducers generate distinct pathological chains and observation windows based on their targets and tissue susceptibility. Within ethical and biosafety frameworks, fixing animal background, administration route, dose normalization, time windows, and control workflows is a prerequisite for obtaining reproducible phenotypes and mechanistically interpretable evidence.
Keywords: hypertension modeling; colitis-associated colorectal cancer (CAC) modeling; liver tumor modeling; acute kidney injury (AKI) modeling; Parkinson’s disease modeling; Alzheimer’s disease modeling; diabetes modeling; hyperlipidemia modeling; hyperuricemia modeling; immune/inflammation modeling; inducible gene regulation models
I. Hypertension Modeling: Ang II and L-NAME
1.1 Overview of Hypertension
Hypertension is a chronic disease state characterized by persistent elevation of arterial blood pressure. Its pathogenesis is multifactorial and commonly involves activation of the renin–angiotensin–aldosterone system (RAAS), dysregulated sympathetic control, altered renal sodium–water handling, endothelial dysfunction, and pathways related to inflammation and oxidative stress.
1.2 Overview of Animal Models of Hypertension
Hypertension models are used to establish a stable blood-pressure elevation phenotype under controlled conditions for mechanistic studies and intervention assessments. Phenotyping typically relies on longitudinal blood pressure monitoring and is supported by vascular functional assays, histology, and molecular readouts. Study design should include baseline blood pressure collection before modeling, fixed measurement time windows and operators, and minimization of stressors (handling, environmental noise, temperature fluctuation) that can distort blood pressure readouts.
1.3 Angiotensin II (Ang II)-Induced Hypertension Model
(1) Model positioning
The Ang II model is based on sustained exogenous Ang II stimulation and is used to mimic a pressor phenotype driven by enhanced RAAS effector signaling.
(2) Pathogenic mechanisms and phenotypic features
① Vasoconstriction and increased peripheral resistance: Ang II activates the angiotensin II type 1 receptor (AT1R), inducing constriction of small arteries and resistance vessels, thereby increasing peripheral resistance and elevating blood pressure.
② Neurohumoral and renal involvement: Ang II can enhance sympathetic activity and increase renal sodium and water reabsorption, further strengthening pressor effects.
③ Oxidative stress–inflammation–remodeling axis: Ang II activates NADPH oxidases and increases reactive oxygen species (ROS) generation, promoting endothelial dysfunction, inflammation, and vascular smooth muscle phenotypic shifts. Beyond blood pressure elevation, the model often shows vascular wall thickening, medial remodeling, and increased collagen deposition.
(3) Experimental workflow (for reference only)
① Animals and baseline: commonly male mice, 8–12 weeks; acclimation ≥7 days; record body weight and collect baseline blood pressure (tail-cuff or telemetry).
② Administration: subcutaneous implantation of osmotic pumps for continuous Ang II infusion; controls receive identical pumps filled with vehicle at matched volume.
③ Dose and duration: continuous infusion at 200–1,000 ng/kg/min for 2–4 weeks, depending on endpoints; a small dose-tier pilot is recommended to define a window that yields stable hypertension while meeting welfare requirements.
④ Dose calculation and solution preparation:
a) Target: convert “target dose (ng/kg/min)” to “per-animal daily dose.”
b) Conversion: target dose × body weight = dose per minute; dose per minute × 1,440 = dose per day; daily dose ÷ pump daily release volume = working concentration.
c) Preparation notes: vehicle often sterile saline; sterile-filter; minimize freeze–thaw; pump filling and surgery under aseptic conditions; prime the pump per manufacturer instructions.
⑤ Postoperative care: monitor incision, body weight, food/water intake, and activity closely for 24–48 h; implement predefined humane endpoints per institutional policy.
(4) Suggested phenotype validation
① Blood pressure: document magnitude, onset, and plateau; consider circadian variation where relevant.
② Vascular structure: quantify wall thickness, media-to-lumen metrics, collagen deposition, and fibrosis to capture remodeling.
③ Molecular readouts: build a traceable mechanistic chain around AT1R downstream signaling, oxidative stress, and inflammatory markers.
1.4 L-NAME-Induced Hypertension Model
(1) Model positioning
The L-NAME model is based on inhibition of endothelial nitric oxide synthase (NOS) and is used to mimic an endothelial dysfunction–associated pressor phenotype driven by reduced NO bioavailability.
(2) Pathogenic mechanisms and phenotypic features
① Reduced NO generation and impaired vasodilation: NOS inhibition decreases NO production, weakening endothelium-dependent vasodilation and shifting tone control toward vasoconstriction.
② Vascular reactivity imbalance and increased peripheral resistance: disrupted relax–contract balance increases peripheral resistance, elevating blood pressure.
③ Amplified oxidative stress and endothelial injury: decreased NO bioavailability can reinforce increased ROS generation, aggravating endothelial dysfunction and inflammation; in some settings, small-artery remodeling and fibrosis are observed.
(3) Experimental workflow (for reference only)
① Animals and baseline: commonly male rats, 200–250 g; record body weight and baseline blood pressure.
② Route A (drinking water; suitable for chronic stable modeling): 20–60 mg/kg/day as the sole drinking source for 4–8 weeks; replace freshly prepared water every 2–3 days and record intake for back-calculation of actual dose.
③ Route B (gavage or injection; strict dose control): 20–50 mg/kg/day once daily for 4 weeks; controls receive matched vehicle volume with identical handling frequency to control stress.
④ Endpoint assessments: body weight, blood pressure, heart rate; serum biochemistry (may include creatinine, BUN, electrolytes); vascular function and histology as needed.
(4) Suggested phenotype validation
① Blood pressure: prioritize dynamics and plateau; track early-phase rise rate after initiation.
② Vascular function: compare endothelium-dependent vs endothelium-independent relaxation to separate endothelial from smooth muscle contributions.
③ Mechanistic readouts: integrate NO-related metabolic indices with oxidative stress and inflammation markers to support an endothelial dysfunction pathway interpretation.
1.5 Method Selection and Application Notes
Modeling approach | CAS No. | Mechanistic focus | Key phenotype emphasis | Suitable research directions | Core validation endpoints |
Ang II induction | RAAS–AT1R axis enhancement; vasoconstriction and pro-remodeling signaling | Clear pressor effect; vascular remodeling/fibrosis often prominent | RAAS mechanisms; vascular remodeling and fibrosis; target-organ injury pathways | Blood pressure dynamics and plateau; vascular remodeling histology; inflammation/oxidative stress/fibrosis markers | |
L-NAME induction | NOS inhibition → reduced NO; endothelial dysfunction | Impaired endothelium-dependent relaxation; abnormal vascular reactivity | Endothelial dysfunction mechanisms; NO pathway; intervention evaluation for vascular function | Blood pressure dynamics and plateau; endothelium-dependent vs -independent relaxation; NO metabolism and oxidative stress/inflammation readouts |
II. Tumor Modeling: DSS-Associated CAC and DEN-Associated Liver Tumors
2.1 Colorectal Cancer Modeling: DSS-Associated Colitis-Associated Cancer (CAC)
(1) Overview of colorectal cancer
Colorectal cancer development is associated with accumulated genetic alterations in epithelial cells, persistent inflammatory microenvironments, barrier disruption, and immune dysregulation. Different models emphasize different links, such as inflammation-driven tumor promotion, abnormal proliferation during damage–repair, and tumor microenvironment/immune infiltration changes.
(2) Overview of animal models
DSS-associated models are commonly used to establish a CAC background. DSS primarily drives mucosal barrier injury and inflammation. To improve tumor incidence and consistency, a mutagenic initiator is often combined to form an “initiation–promotion” sequence.
(3) Model positioning
This model uses epithelial barrier injury and recurrent inflammation as the core background to study inflammation-promoted tumorigenesis and to evaluate anti-inflammatory, immunomodulatory, and microenvironmental interventions on tumor burden and pathological grade.
(4) Pathogenic mechanisms and phenotypic features
① Barrier disruption and mucosal inflammation: DSS induces epithelial injury and mucosal inflammation, producing repeated damage–repair cycles.
② Abnormal proliferation and lesion progression: persistent inflammatory stimulation enhances epithelial proliferation and tissue remodeling, promoting dysplasia and tumor-associated lesions.
③ Endpoint evaluation: inflammation severity and tumor burden should be assessed in parallel, including colon length, histological inflammation scores, lesion number/size/distribution, and pathological grade.
(5) Experimental workflow (for reference only)
① Consistency control: DSS shows lot-to-lot variability; use one lot within a study; perform concentration titration when switching lots to match prior inflammatory intensity.
② Typical AOM/DSS workflow (commonly used to improve consistency):
a) Day 0: AOM i.p. injection, 10 mg/kg once.
b) From day 5: 2.0%–2.5% DSS in drinking water for 5 days, followed by 16 days of regular water.
c) Repeat DSS cycles for 3 rounds; common endpoints at weeks 8–12 (adjustable by study aims).
③ Monitoring: record body weight, stool characteristics, and fecal blood daily; fix DSS replacement frequency and preparation workflow; execute humane endpoints when preset weight-loss thresholds or severe distress occur.
④ Terminal collection and counting: flush colon with PBS, open longitudinally and lay flat; record colon length; count macroscopic tumors and measure diameters; use standardized segment labeling to support distribution analyses.
(6) Suggested phenotype validation
① Tumor burden: lesion count, maximal diameter, distribution, and integrated burden metrics (count plus size).
② Inflammation and histology: colon length, histological inflammation score; pathological grading (dysplasia, adenoma/adenocarcinoma per predefined criteria).
③ Molecular and immune microenvironment: inflammatory cytokine profiles, proliferation/apoptosis markers, immune infiltration features (selected per objectives).
2.2 Liver Tumor Modeling: DEN-Induced Model
(1) Overview of liver tumors
Research often focuses on primary liver malignancies such as hepatocellular carcinoma. Tumorigenesis is linked to mutational accumulation, chronic inflammation and regenerative contexts, and metabolic/immune microenvironment remodeling. Chemical carcinogenesis models provide a time-sequenced “initiation–promotion–progression” process suitable for stage-specific mechanistic studies and intervention evaluation.
(2) Overview of animal models
DEN is a classical chemical carcinogen model with long latency. Outcomes are sensitive to strain, sex, and dosing window. Design should emphasize standardized husbandry and stratified records to ensure comparable incidence and tumor burden.
(3) Model positioning
This model uses chemical mutagenesis as an initiating event to generate liver tumor development and progression phenotypes for studying initiation, clonal expansion, nodule formation, and contributions of inflammation, repair, and microenvironmental factors.
(4) Pathogenic mechanisms and phenotypic features
① Mutagenic initiation: metabolically activated DEN induces DNA damage and mutational accumulation, establishing initiation events.
② Promotion and progression: clonal expansion occurs under hepatocyte proliferation and tissue repair, forming nodules that progress to tumors.
③ Strong influencing factors: strain, sex, dosing timing, and exposure intensity significantly affect incidence and nodule burden.
(5) Experimental workflow (for reference only)
① Animals: commonly male mice; recommend littermate randomization and recording birth dates.
② Dosing (classic single-dose, long-latency design): around postnatal day 14, a single i.p. injection of DEN 25 mg/kg; controls receive matched vehicle volume; maintain until 8–10 months for tumor assessment.
③ Safety and compliance: DEN is a potent carcinogen; preparation, dosing, and waste disposal must comply with institutional chemical safety and biosafety rules.
④ Longitudinal records: monthly body weight, general condition, and mortality; optional staged sampling for liver injury and inflammation background.
(6) Suggested phenotype validation
① Tumor burden: number of surface nodules, maximal nodule diameter, distribution; liver weight/body weight ratio as an auxiliary metric.
② Histology and molecular pathology: H&E-based classification/grading; proliferation/apoptosis readouts; pathway markers as needed.
③ Injury background: serum liver function markers and hepatic inflammation/fibrosis (selected per objectives).
2.3 Method Selection and Application Notes
Modeling reagent/method | CAS No. | Recommended animals and assessment window | Common route and key parameters | Primary readouts and decision points |
DSS-associated CAC (often combined with AOM) | Mice; endpoint at 8–12 weeks | AOM 10 mg/kg i.p. once; 2.0%–2.5% DSS water for 5 days then 16 days recovery, 3 cycles; strict lot consistency and titration | Tumor count/max diameter/distribution; colon length; inflammation score; pathological grading | |
DEN liver tumor | Mice; assess at 8–10 months | ~P14 DEN 25 mg/kg i.p. once; long-term husbandry with stratified records; strict safety compliance | Surface nodule count/max diameter/distribution; liver weight/body weight; H&E classification/grading; liver function and inflammatory background |
III. Acute Kidney Injury Modeling: Cisplatin Model
3.1 Overview of AKI
Acute kidney injury (AKI) is characterized by rapid decline in glomerular filtration with progression of azotemia and may include disturbances in water/electrolyte and acid–base balance. Pathology commonly involves tubular epithelial injury with necrosis/apoptosis, renal microcirculatory impairment, inflammatory cell infiltration, and increased oxidative stress.
3.2 Overview of Animal Models
AKI models reproduce acute renal functional decline with histological and molecular pathology changes to support mechanism dissection and intervention evaluation. Common strategies include ischemia–reperfusion, drug/toxin induction (e.g., cisplatin), and sepsis-associated models. Evaluation typically centers on renal function indices coupled with histology and molecular injury markers, with supportive monitoring of body weight, intake, and general status.
3.3 Cisplatin-Induced AKI Model
(1) Model positioning
A classical drug-induced kidney injury model that mimics chemotherapy-related nephrotoxicity and acute tubular injury, suitable for studying the tubular injury–inflammation–oxidative stress axis, modes of cell death, and repair responses.
(2) Pathogenic mechanisms and phenotypic features
① Tubular epithelial injury as the core: cisplatin accumulates in proximal tubular cells, inducing DNA damage and mitochondrial dysfunction, triggering cell death and barrier disruption.
② Amplified inflammation and oxidative stress: increased ROS, cytokine upregulation, and immune infiltration exacerbate injury and influence repair quality.
③ Concordant functional and histological changes: elevated serum creatinine and BUN, increased urinary injury markers, and tubular dilation, brush border loss, cast formation, and interstitial inflammation.
(3) Experimental workflow (for reference only)
① Animals and baseline: commonly C57BL/6 mice; unify sex and age; record body weight; baseline serum biochemistry optional.
② Regimen A (acute injury; commonly used): single i.p. cisplatin 15–20 mg/kg; controls receive matched saline; typical sampling window 48–96 h (72 h often used as a main timepoint).
③ Regimen B (subacute/chronic injury; for repair observation): i.p. 2.5–5 mg/kg once weekly for 3–4 weeks; controls receive matched vehicle.
④ Supportive care and welfare control:
a) Standardize hydration (subcutaneous fluids if needed) to reduce dehydration confounding.
b) Provide softened food and warming to reduce intake drop and temperature fluctuation.
c) Apply humane endpoints strictly to avoid non-specific terminal-stage bias.
3.4 Method Selection and Application Notes
Modeling reagent | CAS No. | Common regimens | Key process controls | Core readouts |
Cisplatin | Acute: 15–20 mg/kg i.p. once, sample at 48–96 h; Subacute: 2.5–5 mg/kg i.p. weekly × 3–4 weeks | Standardize age/sex; fixed sampling timepoints; hydration and husbandry support as needed; strict humane endpoints | Creatinine/BUN; KIM-1/NGAL; tubular injury scoring and inflammation/oxidative stress readouts |
IV. Neurodegenerative Disease Modeling: Parkinson’s Disease and Alzheimer’s Disease
4.1 Overview
Neurodegenerative diseases feature progressive injury and functional decline of specific neuronal populations and commonly involve aberrant protein aggregation, mitochondrial dysfunction, oxidative stress, neuroinflammation, and reduced synaptic plasticity. Models driven by different pathogenic links enable in vivo reproduction of key phenotypes for mechanistic studies and intervention evaluation.
4.2 Overview of Animal Models
Parkinson’s disease (PD) models typically emphasize nigrostriatal dopaminergic pathway injury and motor phenotypes. Alzheimer’s disease (AD) models often emphasize Aβ-associated neurotoxicity, synaptic dysfunction, and cognitive deficits. Phenotyping generally combines behavioral outputs with neurochemical and histological evidence.
4.3 PD Modeling: MPTP Model
(1) Model positioning
A classic dopaminergic neurotoxin-induced model simulating nigral dopaminergic neuron injury and striatal dopamine depletion, suitable for studying mitochondrial dysfunction, oxidative stress, and neuroinflammation, as well as neuroprotection and pharmacodynamic evaluation.
(2) Mechanisms and phenotypes
① Selective dopaminergic injury: active metabolites enter dopaminergic neurons and impair pathway function.
② Mitochondrial and oxidative stress changes: respiratory chain dysfunction with increased oxidative stress triggers inflammation and cell death.
③ Behavioral and histological outputs: reduced motor coordination, decreased TH-positive neurons, decreased striatal dopamine.
(3) Experimental workflow (for reference only)
① Animals: male C57BL/6 mice, 7–10 weeks; acclimation ≥7 days.
② Acute regimen (commonly used): i.p. MPTP 20 mg/kg every 2 h, 4 injections total; controls receive matched vehicle; prepare working solution fresh on dosing day and fix injection timepoints.
③ Management and disposal: short-term isolation after dosing; treat excreta/bedding/instruments as high-risk toxin waste; fix behavioral testing and tissue collection timepoints.
(4) Suggested phenotype validation
① Behavior: rotarod, open field, pole test (as needed).
② Neurochemistry/histology: TH immunostaining quantification; striatal dopamine and metabolites.
③ Inflammation/oxidative stress: microglial activation markers and oxidative stress indices (as needed).
4.4 PD Modeling: 6-OHDA Model
(1) Model positioning
A focal dopaminergic neurotoxicity model typically established by stereotaxic intracranial injection to generate unilateral nigrostriatal injury, enabling stable lateralized phenotypes and quantitative intervention assessment.
(2) Mechanisms and phenotypes
① Oxidative stress-driven neurotoxicity damages dopaminergic terminals and cell bodies.
② Unilateral injury yields characteristic rotational behavior for quantifying lesion severity.
③ Histology: consistent reductions in TH-positive neurons and striatal fiber density.
(3) Experimental workflow (for reference only)
① Animals: mice 8–10 weeks; acclimation ≥7 days.
② Solution preparation: prepare 6-OHDA fresh; vehicle is sterile saline plus ascorbic acid to reduce oxidation; protect from light.
③ Stereotaxic injection (parameter framework):
a) Target region: striatum, medial forebrain bundle, or substantia nigra; fix target and coordinate system within a study.
b) Dose design: 2–6 µg per side total (via concentration–volume combinations; multi-site injection as needed).
c) Injection rate: 0.1–0.5 µL/min; keep needle in place 5–10 min post-injection to reduce backflow.
④ Postoperative care: warming recovery and analgesia; intensive monitoring for 72 h; behavioral testing typically at 2–4 weeks post-surgery.
(4) Suggested phenotype validation
① Behavior: apomorphine- or amphetamine-induced rotations plus motor tests (as needed).
② Histology: TH immunostaining quantification in substantia nigra and striatum.
③ Neuroinflammation/synapse: glial activation and synaptic protein indices (as needed).
4.5 PD Modeling: Rotenone Model
(1) Model positioning
A mitochondrial dysfunction–driven model suitable for studying mitochondrial toxicity, oxidative stress, proteostasis imbalance, and neuroinflammation, and for exploring environmental toxin–related risk factors.
(2) Mechanisms and phenotypes
① Mitochondrial respiratory chain inhibition induces energetic failure and oxidative stress.
② Broad toxicity and high variability require stringent dose control and monitoring.
③ PD-relevant outputs include motor decline with dopaminergic pathway injury and inflammatory changes.
(3) Experimental workflow (for reference only)
① One implementation to reduce exposure fluctuation: continuous subcutaneous delivery via osmotic pumps at 2.0–2.5 mg/kg/day for 4 weeks; controls receive matched vehicle.
② Monitoring: weekly body weight, general status, and motor function; predefined humane endpoints.
③ Consistency: fixed solvent system, preparation workflow, and dosing schedule; use a pilot to calibrate tolerability and phenotype strength if needed.
(4) Suggested phenotype validation
① Behavior: coordination, activity, and fine motor tests (as needed).
② Histology/neurochemistry: TH quantification and dopamine measurement.
③ Systemic toxicity: body weight, general condition, and organ toxicity readouts as designed.
4.6 AD Modeling: Aβ25–35 Model
(1) Model positioning
Aβ25–35 is a commonly used short peptide fragment to model Aβ-related neurotoxicity, mainly to mimic Aβ-induced synaptic dysfunction, neuroinflammation, and learning/memory impairment, suitable for rapid validation and mechanistic screening.
(2) Mechanisms and phenotypes
① Oligomerization/aggregation-associated toxicity impairs synaptic plasticity and triggers inflammation.
② Learning and memory behavioral abnormalities.
③ Decreased synaptic proteins with increased inflammatory cytokines and oxidative stress.
(3) Experimental workflow (for reference only)
① Peptide pretreatment consistency: fix dissolution system, pre-aggregation conditions, aliquoting, and freeze–thaw cycles; use one batch where possible and assess consistency.
② Administration: intracerebroventricular or hippocampal injection; volume 2–5 µL; slow infusion with 5-min dwell time to reduce reflux.
③ Dose: design low/high groups at nmol-per-animal scale; include matched solvent control or scrambled peptide control (as needed).
④ Observation window: behavioral testing typically 1–4 weeks post-injection with fixed order and timepoints.
(4) Suggested phenotype validation
① Behavior: Morris water maze, Y-maze, novel object recognition (as needed).
② Synapse/neuroinflammation: synaptic proteins and glial activation markers.
③ Molecular/pathology: Aβ-related assays and oxidative stress indices (as needed).
4.7 AD Modeling: Aβ1–42 Model
(1) Model positioning
Aβ1–42 shows stronger aggregation propensity and is used to model phenotypes closer to oligomer toxicity and deposition, suitable for studying links among Aβ aggregation, synaptic injury, neuroinflammation, and cognitive deficits.
(2) Mechanisms and phenotypes
① Formation of oligomeric/fibrillar aggregates inducing synaptic dysfunction.
② Cognitive behavioral abnormalities with commonly used synaptic readouts.
③ More pronounced glial activation and cytokine upregulation.
(3) Experimental workflow (for reference only)
① Peptide preparation consistency: fix de-aggregation, film formation, re-dissolution, dilution, and oligomerization conditions; avoid light and minimize mechanical agitation; unify batch and workflow within a study.
② Administration: intracerebroventricular or hippocampal injection; 2–5 µL; slow infusion with 5–10 min dwell time.
③ Dose: design at µg-per-animal scale with matched solvent fraction and injection parameters in controls.
④ Observation window: commonly 1–6 weeks post-injection for behavioral and histological assessments; fix testing timepoints and tissue collection workflows.
(4) Suggested phenotype validation
① Behavior: combined learning/memory tests with longitudinal tracking where needed.
② Aβ-related: deposition/oligomer assays and synaptic injury indices.
③ Inflammation/cell death: glial activation and cell death pathway readouts (as needed).
4.8 Method Selection and Application Notes
Modeling reagent | CAS No. | Primary disease | Model emphasis | Key advantages | Major limitations and notes |
MPTP hydrochloride | Parkinson’s disease | Systemic dopaminergic injury; mitochondrial/oxidative stress | Clear phenotypes; suitable for mechanism and pharmacodynamics | Sensitive to strain/sex/regimen; stringent safety and waste disposal | |
6-OHDA hydrobromide | Parkinson’s disease | Focal unilateral lesion; rotation behavior | High reproducibility; quantitative readouts | Requires stereotaxic surgery; postoperative care and parameter consistency are critical | |
Rotenone | Parkinson’s disease | Mitochondrial toxicity and chronic injury | Fits mitochondrial and environmental toxin research | High variability and systemic toxicity; intensified monitoring and ethical endpoints needed | |
Aβ25–35 (human) | Alzheimer’s disease | Aβ-related neurotoxicity and synaptic injury | Relatively short cycle; suitable for screening | Sensitive to peptide pretreatment and dosing parameters; control batch variability | |
Aβ1–42 (human) | Alzheimer’s disease | Aβ aggregation/oligomer toxicity and cognitive deficits | Closer to aggregation-linked mechanisms | Dissolution/aggregation conditions are decisive; high demands on consistency management |
V. Metabolic Disease Modeling: STZ, Cholesterol/High-Fat Diets, and Adenine-Related Regimens
5.1 Overview of Metabolic Diseases
Metabolic diseases reflect disrupted homeostasis of glucose, lipid, and purine metabolism and can drive systemic metabolic remodeling and multi-organ dysfunction. Animal models typically follow a “pathway perturbation → core metabolic index abnormality → histological and molecular phenotype changes” logic for mechanistic and intervention studies.
5.2 Overview of Animal Models
Modeling strategies include chemical induction, dietary interventions, or combinations. Evaluation centers on core indices: diabetes on glucose and β-cell function; hyperlipidemia on lipid panels plus hepatic lipid phenotypes; hyperuricemia on serum urate plus renal function and inflammation readouts where needed. Design should emphasize balanced baseline, consistent dosing/feeding, fixed sampling timepoints, and consistent assay platforms.
5.3 Diabetes Modeling: STZ Model
(1) Model positioning
The STZ model produces hyperglycemia driven by pancreatic β-cell injury and reduced insulin secretion. Different dosing strategies yield different severity and temporal trajectories.
(2) Mechanisms and phenotypes
① β-cell injury and reduced insulin secretion leading to sustained hyperglycemia and impaired glucose tolerance.
② Systemic phenotypes such as body weight change and altered water/food intake.
③ Islet morphology and β-cell marker shifts corroborate metabolic readouts.
(3) Experimental workflow (for reference only)
① Preparation: STZ is unstable; prepare fresh on ice; commonly use citrate–citrate buffer (pH ~4.4–4.5); fix preparation temperature and the time window from preparation to injection completion.
② High-dose single injection (often for type 1–like phenotype): after fasting, a single i.p. injection 100–150 mg/kg; model assessment window typically 5–7 days later.
③ Multiple low-dose injections (reduced acute toxicity; useful for immune-related studies): i.p. 40–60 mg/kg/day for multiple consecutive days; assessment window depends on regimen.
④ Model confirmation: fix sampling timepoints; fasting or random glucose exceeding preset thresholds for a defined duration can be used; add GTT and insulin-related readouts as needed.
(4) Suggested phenotype validation
① Glucose-related: fasting/random glucose; glucose tolerance tests; insulin and C-peptide (as needed).
② Body and intake: body weight, water intake, food intake.
③ Histology/molecular: islet morphology and β-cell markers.
5.4 Hyperlipidemia Modeling: Cholesterol/High-Fat Diet Models
(1) Model positioning
Dietary interventions induce dyslipidemia for studying lipid metabolism disorders and intervention effects.
(2) Mechanisms and phenotypes
① Increased exogenous lipid load drives lipid panel abnormalities.
② Hepatic lipid accumulation and lipid-metabolism molecular changes often accompany dyslipidemia.
③ Time-to-phenotype and severity depend on diet formulation, feeding duration, and animal background.
(3) Experimental workflow (for reference only)
① Rapid induction (short window): cholesterol 1%–2% (w/w) + fat source ~10% (w/w) + basal diet for 7–14 days.
② Stable induction (mid/long window): high-fat diet providing 45% or 60% calories from fat for 4–12 weeks; optionally add 0.2%–1% cholesterol (w/w) to strengthen cholesterol load.
③ Process control: fix blood collection timing and fasting duration (if used); record food intake and body weight curves; use the same diet batch throughout the study period.
(4) Suggested phenotype validation
① Lipid panel: TC, TG, LDL-C, HDL-C, etc.
② Liver phenotypes: liver weight/body weight, hepatic lipid content, histological steatosis.
③ Controls: matched normal diet controls; baseline measurements for within-animal correction when applicable.
5.5 Hyperuricemia Modeling: Adenine-Related Regimens
(1) Model positioning
Adenine-related regimens are used to construct purine-load–related abnormalities that can elevate serum urate and, under some conditions, produce renal injury phenotypes. These models support studies on urate-associated inflammation, oxidative stress, renal pathway changes, and intervention evaluation.
(2) Mechanisms and phenotypes
① Elevated serum urate after treatment, sometimes accompanied by renal function abnormalities and renal pathology (depending on regimen intensity and duration).
② Phenotype strength and time course depend on dose, schedule, and animal background; confirmation should rely on dynamic monitoring.
(3) Experimental workflow (for reference only)
① Animals: adult male rats.
② Example dosing framework: adenine 200–250 mg/kg/day by gavage for 3–4 weeks; for combination regimens, fix co-medications, doses, and dosing order; include single-agent and combination groups for interpretability.
③ Dynamic monitoring: serum urate at days 7/14/21/28, with concurrent creatinine, BUN, and renal histology to support consistent “urate–kidney injury axis” adjudication.
(4) Suggested phenotype validation
① Metabolic index: serum urate with time-course curves.
② Associated readouts: renal function biochemistry; inflammation/oxidative stress markers; renal histology.
5.6 Method Selection and Application Notes
Modeling reagent | CAS No. | Target disease | Common experimental path | Model confirmation and core readouts |
STZ (streptozotocin) | Diabetes | Single high-dose or multiple low-dose injections; fresh preparation in acidic buffer | Blood glucose and tolerance; body weight and intake; pancreatic islet histology | |
Cholesterol/high-fat diet | Hyperlipidemia | High-fat or high-cholesterol feeding; short or mid/long regimens | TC/TG/LDL-C/HDL-C; hepatic lipid accumulation and histology | |
Adenine | Urate-related abnormalities | Gavage dosing for 3–4 weeks (optional combination regimens) | Serum urate dynamics; creatinine/BUN; renal pathology |
VI. Immune/Inflammation Modeling: PMA, R-848, and Imiquimod
6.1 Overview of Immune/Inflammatory Diseases
Immune and inflammatory diseases are driven by imbalance between innate and adaptive responses and manifest as dysregulated cytokine networks, enhanced recruitment/activation of immune cells, barrier dysfunction, or immune-mediated organ injury. Animal models often follow an “immune activation signal → inflammatory cascade → tissue pathology and functional abnormality” framework for mechanistic and intervention studies.
6.2 Overview of Animal Models
Immune/inflammation models commonly use immunostimulants to induce local tissue inflammation via localized administration, or antigen immunization to induce organ-specific inflammation. Evaluation typically centers on inflammation severity and immune lineage changes, combined with histopathology, serum cytokines, and functional readouts.
6.3 PMA-Induced Immune Activation/Inflammation Model
(1) Model positioning
PMA is a PKC agonist used to induce immune cell activation in vitro and to model localized inflammatory responses in vivo for studying inflammatory signal transduction and cell recruitment.
(2) Mechanisms and phenotypes
① PKC activation promotes downstream MAPK/NF-κB signaling and induces inflammatory cytokines.
② Local erythema, swelling, infiltration, and histological inflammation (depending on site and regimen).
③ Inflammation intensity can be tuned by dose and time windows.
(3) Experimental workflow (for reference only)
① In vitro stimulation : PMA 10–100 nM for 24–72 h to drive monocyte-to-macrophage-like differentiation; replace medium and rest for 24–48 h; include unstimulated and solvent controls.
② In vivo localized inflammation : topical application on skin/ear to induce short-term inflammation; fix area, dose, and measurement timepoints; quantify edema by ear thickness or biopsy weight, supported by histology and cytokines.
(4) Suggested phenotype validation
① Cytokines: TNF-α, IL-1β, IL-6, and downstream signals.
② Cellular: activation markers and infiltration lineage shifts.
③ Histology: inflammation scoring and morphological readouts.
6.4 R-848-Induced Innate Immune Activation and Inflammation Models
(1) Model positioning
R-848 is a TLR7/8 agonist that induces innate immune activation–dominant inflammation phenotypes and can produce organ immune injury readouts under certain regimens, suitable for studying TLR-driven inflammation, immune infiltration, and tissue damage.
(2) Mechanisms and phenotypes
① Induces type I interferons and multiple inflammatory cytokines, driving recruitment and activation.
② Organ injury readouts depend on dose, frequency, and observation windows.
③ Clear immune lineage changes support mechanism dissection and intervention evaluation.
(3) Experimental workflow (for reference only)
① Systemic dosing (acute framework): i.p. 50–100 µg per animal, single or short-course; controls receive matched vehicle; sample at hours and 24 h for acute dynamics.
② Topical dosing (chronic framework): apply to ear/back skin at fixed dose and area, multiple times per week over weeks to generate chronic inflammation; controls receive matched base/vehicle.
③ Assessment: stratify timepoints and analyze histology, serum factors, and immune lineage profiles to strengthen adjudication consistency.
(4) Suggested phenotype validation
① Tissue inflammation/damage: histological scores and injury markers (as needed).
② Functional: organ-specific functional parameters (as applicable).
③ Mechanism: TLR7/8 downstream signaling, type I IFN pathways, cytokine profiles, and immune infiltration lineage analysis.
6.5 Imiquimod-Induced Psoriasis-Like Dermatitis Model
(1) Model positioning
Imiquimod is a TLR7 agonist; topical application induces psoriasis-like dermatitis characterized by hyperkeratosis, epidermal thickening, and IL-23/IL-17–axis inflammation, suitable for psoriasis mechanism and pharmacodynamics.
(2) Mechanisms and phenotypes
① Innate immune activation drives inflammatory cascades and Th17-related pathway activation.
② Prominent erythema, scaling, and thickening; histology shows epidermal hyperplasia and inflammatory infiltration.
③ Combine clinical-like scoring with histological and molecular readouts for adjudication.
(3) Experimental workflow (for reference only)
① Regimen: shave dorsal skin and apply 5% formulation once daily for 5–8 days; controls receive the same base.
② Process control: fix application area, time, and duration; optional concurrent ear application for ear thickness readout.
③ Sampling: skin H&E and immunohistochemistry; flow cytometry for infiltrating immune lineages as needed.
(4) Suggested phenotype validation
① Clinical-like scoring: erythema, scaling, thickening.
② Histology: epidermal thickness, keratinization abnormalities, infiltration scoring.
③ Molecular/immune: IL-23/IL-17 axis factors, keratinocyte markers, and infiltration lineages (as needed).
6.6 Method Selection and Application Notes
Modeling reagent | CAS No. | Application area | Key model emphasis | Common core readouts |
PMA | 16561-29-8 | Immune activation/inflammation | PKC activation and cytokine induction | Cytokine profiles, activation markers, tissue inflammation scores |
R-848 (resiquimod) | Innate immune activation/inflammation | TLR7/8-driven activation and inflammatory cascades | IFN/cytokine profiles, immune lineage profiling, histological damage | |
Imiquimod | Psoriasis-like dermatitis | TLR7-driven IL-23/IL-17 axis | PASI-like scoring, epidermal thickness, Th17-related factors and infiltration lineages |
VII. Gene Regulation Models: Doxycycline- and Tamoxifen-Inducible Systems
7.1 Overview
Inducible gene regulation models enable controlled, time-resolved and tissue-specific modulation of target gene expression in vivo or in vitro, supporting gene-function dissection, disease mechanism validation, and reversible phenotype construction. Common strategies include tetracycline-inducible systems (Tet-on/Tet-off) and estrogen receptor–fused recombinase systems (CreERT/ERT2). Design should address induction efficiency, basal leakiness, tissue specificity, induction windows, reversibility, and standardized induction/validation workflows.
7.2 Doxycycline-Inducible Tet Systems
(1) Model positioning
Doxycycline serves as the inducer in Tet systems to switch target gene expression on/off or tune expression levels, enabling reversible, time-controlled studies.
(2) Mechanisms and key phenotype points
① Tet-on: doxycycline binds the transactivator, enabling TRE binding and target gene induction.
② Tet-off: doxycycline inhibits transactivator–TRE binding, turning off or reducing expression.
③ Induction strength and kinetics depend on route, dose, tissue penetration, and transgenic construct design.
(3) Experimental workflow (for reference only)
① Drinking water dosing (common): doxycycline 0.2–2.0 mg/mL gradient for optimization; protect from light; replace every 48 h; record water intake and body weight to assess intake variability.
② Feed dosing (reduces water-intake variability): customized doxycycline diet; fix diet batch and record intake and body weight curves; consider measuring exposure in blood/tissue to calibrate induction.
③ Induction and withdrawal windows: sample multiple timepoints after initiation to build an induction curve; sample after withdrawal to build a decay curve; keep sampling timepoints consistent within a study.
(4) Validation recommendations
① Expression: qPCR, Western blot, immunostaining, or reporter signals.
② Leakiness: uninduced controls and littermate controls in parallel.
③ Tissue distribution: target vs non-target tissues to evaluate specificity and spillover.
7.3 Tamoxifen-Inducible CreERT/ERT2 Systems
(1) Model positioning
Tamoxifen activates ER ligand-binding domain–fused Cre recombinase, enabling time-controlled recombination/knockout/knock-in at loxP sites, suitable for triggering recombination at specific developmental stages or timepoints.
(2) Mechanisms and key phenotype points
① Tamoxifen binding drives CreERT/ERT2 nuclear translocation and loxP recombination.
② Recombination efficiency depends on promoter activity, tissue penetration, and dosing regimen; tissue differences can be substantial.
③ Recombination is irreversible; the induction window defines the onset of stable genetic change.
(3) Experimental workflow (for reference only)
① Solution preparation: commonly dissolved in corn oil; typical 10–20 mg/mL; protect from light; use the same preparation batch across an induction cycle where possible.
② Adult mouse dosing framework: i.p. once daily for 3–5 consecutive days or alternate-day multi-dose schedules; optimize via pilot to balance sufficient recombination and tolerability.
③ Sampling timing: set a fixed interval after the last dose (e.g., 3–14 days) for recombination validation and phenotyping to avoid group incomparability from kinetic differences.
④ Controls: include “Cre-negative + tamoxifen” controls to separate drug effects from recombination effects.
(4) Validation recommendations
① Recombination: genomic PCR/sequencing, reporter signals, or target protein loss.
② Tissue specificity: quantify recombination in target and non-target tissues.
③ Confounding control: track body weight, general status, and baseline inflammation indices (as appropriate) to reduce drug toxicity/stress confounding.
7.4 Method Selection and Application Notes
Inducer | CAS No. | Common system | Control type | Key advantages | Key validation points |
Doxycycline hyclate | Tet-on/Tet-off | Reversible expression control | Time-controlled, withdrawable, tunable expression | mRNA/protein kinetics; leakiness assessment; tissue distribution confirmation | |
Tamoxifen citrate | CreERT/ERT2 | Inducible recombination (irreversible) | Precise timing; suitable for stage-specific studies | Quantify tissue recombination efficiency; reporter/genotyping; drug-only control |
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