Tissue, urine and serum NMR metabolomics dataset from a 5/6 nephrectomy rat model of chronic kidney disease

The Metabolic Profile of Plasma During Epileptogenesis in a Rat Model of Lithium-Pilocarpine-Induced Temporal Lobe Epilepsy

Temporal lobe epilepsy (TLE) arises mostly because of an initial injury. Certain stimuli can make a normal brain prone to repeated, spontaneous seizures via a process called epileptogenesis. This study examined the plasma metabolomics profile in rats with the induced TLE to identify feasible biomarkers that can distinguish progression of epileptogenesis in three different time points and reveal the underlying mechanisms of epileptogenesis. Status epilepticus (SE) was induced by repetitive intraperitoneal injections of low-dose lithium chloride-pilocarpine hydrocholoride. Blood samples were collected 48 h, 1 week, and 6 weeks after SE, respectively. Plasma metabolites were analyzed by nuclear magnetic resonance (NMR) spectrometry. Statistical analysis was performed using MetaboAnalyst 6.0. An orthogonal partial least squares discriminant analysis (OPLS-DA) model was employed to represent variations between the TLE model groups and respective controls. Volcano plot analysis was used to identify key features, applying a fold-change criterion of 1.5 and a t-test threshold of 0.05. 48 h after SE, dimethyl sulfone (DMSO2) and creatinine levels were decreased, whereas glycine and creatine levels were increased. The only metabolite that changed 1 week after SE was pyruvic acid, which was increased compared to its control level. Lactic acid, pyruvic acid, and succinic acid levels were increased 6 weeks after SE. The identified metabolites were especially related to the tricarboxylic acid cycle and glycine, serine, and threonine metabolism. The results illustrate that distinct plasma metabolites can function as phase-specific biomarkers in TLE and reveal new insights into the mechanisms underlying SE.

Effects of Probiotic-Enriched Minas Cheese (Lactobacillus acidophilus La-05) on Cardiovascular Parameters in 5/6 Nephrectomized Rats

Dairy foods have become an interest in chronic kidney disease (CKD) due to their nutritional profile, which makes them a good substrate for probiotics incorporation. This study evaluated the effect of probiotic-enriched Minas cheese with Lactobacillus acidophilus La-05 in an experimental rat model for CKD on cardiac, inflammatory, and oxidative stress parameters. Male Wistar rats were divided into 4 groups (n = 7/group): 5/6 nephrectomy + conventional Minas cheese (NxC); 5/6 nephrectomy + probiotic Minas cheese (NxPC); Sham + conventional Minas cheese (ShamC); Sham + probiotic Minas cheese (ShamPC). Offering 20 g/day of Minas cheese with Lact. acidophilus La-05 (108-109 log CFU/g) for 6 weeks. The cardiomyocyte diameter was determined. Superoxide dismutase (SOD) activity in plasma, heart, kidney, and colon tissue was performed. At the end of supplementation, no significant changes in lipid profile and renal parameters were found. The NxPC group showed a decrease in cardiomyocyte diameter compared to the NxC group (16.99 ± 0.85 vs. 19.05 ± 0.56 μm, p = 0.0162); also they showed reduced plasmatic SOD activity (502.8 ± 49.12 vs. 599.4 ± 94.69 U/mL, p < 0.0001). In summary, probiotic-enriched Minas cheese (Lact. acidophilus La-05) consumption suggests a promisor cardioprotective effect and was able to downregulate SOD activity in a rat model of CKD.

Urinary Metabolic Profiling During Epileptogenesis in Rat Model of Lithium-Pilocarpine-Induced Temporal Lobe Epilepsy

Background/Objectives: Temporal lobe epilepsy (TLE) often develops following an initial brain injury, where specific triggers lead to epileptogenesis-a process transforming a healthy brain into one prone to spontaneous, recurrent seizures. Although electroencephalography (EEG) remains the primary diagnostic tool for epilepsy, it cannot predict the risk of epilepsy after brain injury. This limitation highlights the need for biomarkers, particularly those measurable in peripheral samples, to assess epilepsy risk. This study investigated urinary metabolites in a rat model of TLE to identify biomarkers that track epileptogenesis progression across the acute, latent, and chronic phases and elucidate the underlying mechanisms. Methods: Status epilepticus (SE) was induced in rats using repeated intraperitoneal injections of lithium chloride-pilocarpine hydrochloride. Urine samples were collected 48 h, 1 week, and 6 weeks after SE induction. Nuclear magnetic resonance spectrometry was used for metabolomic analysis, and statistical evaluations were performed using MetaboAnalyst 6.0. Differences between epileptic and control groups were represented using the orthogonal partial least squares discriminant analysis (OPLS-DA) model. Volcano plot analysis identified key metabolic changes, applying a fold-change threshold of 1.5 and a p-value < 0.05. Results: The acute phase exhibited elevated levels of acetic acid, dihydrothymine, thymol, and trimethylamine, whereas glycolysis and tricarboxylic acid cycle metabolites, including pyruvic and citric acids, were reduced. Both the acute and latent phases showed decreased theobromine, taurine, and allantoin levels, with elevated 1-methylhistidine in the latent phase. The chronic phase exhibited reductions in pimelic acid, tiglylglycine, D-lactose, and xanthurenic acid levels. Conclusions: These findings highlight stage-specific urinary metabolic changes in TLE, suggesting distinct metabolites as biomarkers for epileptogenesis and offering insights into the mechanisms underlying SE progression.

Personalized Metabolic Profile by Synergic Use of NMR and HRMS

A new strategy that takes advantage of the synergism between NMR and UHPLC-HRMS yields accurate concentrations of a high number of compounds in biofluids to delineate a personalized metabolic profile (SYNHMET). Metabolite identification and quantification by this method result in a higher accuracy compared to the use of the two techniques separately, even in urine, one of the most challenging biofluids to characterize due to its complexity and variability. We quantified a total of 165 metabolites in the urine of healthy subjects, patients with chronic cystitis, and patients with bladder cancer, with a minimum number of missing values. This result was achieved without the use of analytical standards and calibration curves. A patient's personalized profile can be mapped out from the final dataset's concentrations by comparing them with known normal ranges. This detailed picture has potential applications in clinical practice to monitor a patient's health status and disease progression.