NMR-based metabolic profiling of urine, serum, fecal, and pancreatic tissue samples from the Ptf1a-Cre; LSL-KrasG12D transgenic mouse model of pancreatic cancer

Statistical considerations and database limitations in NMR-based metabolic profiling studies

INTRODUCTION

Interpretation and analysis of NMR-based metabolic profiling studies is limited by substantially incomplete commercial and academic databases. Statistical significance tests, including p-values, VIP scores, AUC values and FC values, can be largely inconsistent. Data normalization prior to statistical analysis can cause erroneous outcomes.

OBJECTIVES

The objectives were (1) to quantitatively assess consistency among p-values, VIP scores, AUC values and FC values in representative NMR-based metabolic profiling datasets, (2) to assess how data normalization can impact statistical significance outcomes, (3) to determine resonance peak assignment completion potential using commonly used databases and (4) to analyze intersection and uniqueness of metabolite space in these databases.

METHODS

P-values, VIP scores, AUC values and FC values, and their dependence on data normalization, were determined in orthotopic mouse model of pancreatic cancer and two human pancreatic cancer cell lines. Completeness of resonance assignments were evaluated using Chenomx, the human metabolite database (HMDB) and the COLMAR database. The intersection and uniqueness of the databases was quantified.

RESULTS

P-values and AUC values were strongly correlated compared to VIP or FC values. Distributions of statistically significant bins depended strongly on whether or not datasets were normalized. 40-45% of peaks had either no or ambiguous database matches. 9-22% of metabolites were unique to each database.

CONCLUSIONS

Lack of consistency in statistical analyses of metabolomics data can lead to misleading or inconsistent interpretation. Data normalization can have large effects on statistical analysis and should be justified. About 40% of peak assignments remain ambiguous or impossible with current databases. 1D and 2D databases should be made consistent to maximize metabolite assignment confidence and validation.

Metabolic profiling of induced acute pancreatitis and pancreatic cancer progression in a mutant Kras mouse model

Untargeted Nuclear Magnetic Resonance (NMR) metabolomics of polar extracts from the pancreata of a caerulin-induced mouse model of pancreatitis (Pt) and of a transgenic mouse model of pancreatic cancer (PCa) were used to find metabolic markers of Pt and to characterize the metabolic changes accompanying PCa progression. Using multivariate analysis a 10-metabolite metabolic signature specific to Pt tissue was found to distinguish the benign condition from both normal tissue and precancerous tissue (low grade pancreatic intraepithelial neoplasia, PanIN, lesions). The mice pancreata showed significant changes in the progression from normal tissue, through low-grade and high-grade PanIN lesions to pancreatic ductal adenocarcinoma (PDA). These included increased lactate production, amino acid changes consistent with enhanced anaplerosis, decreased concentrations of intermediates in membrane biosynthesis (phosphocholine and phosphoethanolamine) and decreased glycosylated uridine phosphates, reflecting activation of the hexosamine biosynthesis pathway and protein glycosylation.

NMR-based serum and urine metabolomic profile reveals suppression of mitochondrial pathways in experimental sepsis-associated acute kidney injury

Sepsis-associated acute kidney injury (SA-AKI) is a significant problem in the critically ill that causes increased death. Emerging understanding of this disease implicates metabolic dysfunction in its pathophysiology. This study sought to identify specific metabolic pathways amenable to potential therapeutic intervention. Using a murine model of sepsis, blood and tissue samples were collected for assessment of systemic inflammation, kidney function, and renal injury. Nuclear magnetic resonance (NMR)-based metabolomics quantified dozens of metabolites in serum and urine that were subsequently submitted to pathway analysis. Kidney tissue gene expression analysis confirmed the implicated pathways. Septic mice had elevated circulating levels of inflammatory cytokines and increased levels of blood urea nitrogen and creatinine, indicating both systemic inflammation and poor kidney function. Renal tissue showed only mild histological evidence of injury in sepsis. NMR metabolomic analysis identified the involvement of mitochondrial pathways associated with branched-chain amino acid metabolism, fatty acid oxidation, and de novo NAD⁺ biosynthesis in SA-AKI. Renal cortical gene expression of enzymes associated with those pathways was predominantly suppressed. Renal cortical fatty acid oxidation rates were lower in septic mice with high inflammation, and this correlated with higher serum creatinine levels. Similar to humans, septic mice demonstrated renal dysfunction without significant tissue disruption, pointing to metabolic derangement as an important contributor to SA-AKI pathophysiology. Metabolism of branched-chain amino acid and fatty acids and NAD⁺ synthesis, which all center on mitochondrial function, appeared to be suppressed. Developing interventions to activate these pathways may provide new therapeutic opportunities for SA-AKI.NEW & NOTEWORTHY NMR-based metabolomics revealed disruptions in branched-chain amino acid metabolism, fatty acid oxidation, and NAD⁺ synthesis in sepsis-associated acute kidney injury. These pathways represent essential processes for energy provision in renal tubular epithelial cells and may represent targetable mechanisms for therapeutic intervention.

NMR-Based Metabolomics in Cancer Research

Nuclear magnetic resonance (NMR) spectroscopy offers reproducible quantitative analysis and structural identification of metabolites in various complex biological samples, such as biofluids (plasma, serum, and urine), cells, tissue extracts, and even intact organs. Therefore, NMR-based metabolomics, a mainstream metabolomic platform, has been extensively applied in many research fields, including pharmacology, toxicology, pathophysiology, nutritional intervention, disease diagnosis/prognosis, and microbiology. In particular, NMR-based metabolomics has been successfully used for cancer research to investigate cancer metabolism and identify biomarker and therapeutic targets. This chapter highlights the innovations and challenges of NMR-based metabolomics platform and its applications in cancer research.

Differences in Human Milk Lactose and Citrate Concentrations Based on Gestational Diabetes Status

Background: Exclusive breastfeeding is the optimal manner of early infant nutrition but women with gestational diabetes mellitus (GDM) often experience challenges with lactation in the early postpartum period. Increases in the colostral metabolites of lactose and citrate have been found to indicate increased milk production. Materials and Methods: A follow-up study of 133 postpartum women with and without GDM was conducted to examine differences in specific colostral metabolite levels using enzymatic methods to determine transition to lactogenesis II during the first week postpartum. We used linear mixed models for repeated measures over time to examine the effect of GDM on colostral metabolite levels at baseline and follow-up with fixed effects of GDM status, time, covariates, and interactions between time and GDM, between time and time, and between time, time and GDM into the model allowing quadratic trends over time. Results: Over time, lactose and citrate levels increased for all mothers (p < 0.001 and p < 0.001, respectively), although mothers with GDM had consistently lower lactose and citrate levels compared with nondiabetic mothers (p = 0.004 and p = 0.014, respectively). Age, prepregnancy body mass index, mode of birth, and parity did not independently influence colostral concentrations of lactose and citrate. Conclusions: Findings suggest that the rate of change overtime in lactose and citrate concentrations differ by GDM status. Further research examining the trajectory of colostral metabolite levels by GDM status is warranted.

The Effects of Rhein and Honokiol on Metabolic Profiles in a Mouse Model of Acute Pancreatitis

BACKGROUND Acute pancreatitis (AP) is generally a self-limiting inflammatory disease, but is associated with a high mortality rate when severe. The present study aimed to investigate the effects of rhein and honokiol on AP. MATERIAL AND METHODS Thirty mice were randomly divided into 5 groups (n=6 per group): blank control, AP model, AP+rhein, AP+honokiol, and AP+rhein+honokiol. The AP model was prepared by intraperitoneal injection of cerulein and lipopolysaccharide (LPS). We observed the pathological changes of the pancreas by hematoxylin and eosin (H&E) staining. A mouse amylase kit was utilized to detect the level of amylase content in serum. Gas chromatography mass spectrometer analysis was performed to detect the differences in metabolites among the blank control, AP model, and AP+rhein+honokiol groups. RESULTS The serum amylase level was significantly higher in the AP model, which suggested that the AP model was constructed successfully. The AP+rhein+honokiol group had significantly reduced interstitial edema, inflammatory cell infiltration, hemorrhage, and necrosis. In addition, the rhein and honokiol treatment influenced some of the metabolic pathways in AP, including riboflavin metabolism, glycerophospholipid metabolism, linoleic acid metabolism, and the pentose and glucuronate interconversions pathway. CONCLUSIONS This study showed that the combination of rhein and honokiol ameliorated pathological changes in the pancreas of mice with AP.

1H NMR-Based Fecal Metabolomics Reveals Changes in Gastrointestinal Function of Aging Rats Induced by d-Galactose

d-galactose (d-gal) is widely used to induce aging. However, it is still unclear whether long-term injection of d-gal affects the gastrointestinal functions of aging rats, and how. In this study, we investigated the effects of d-gal on the gastrointestinal functions of aging rats, especially from the perspective of fecal metabolomics. Biochemical and behavioral analyses were performed. Besides, a ¹H NMR-based metabolomics approach was built and applied in combination with multivariate data analysis including principal components analysis (PCA) and orthogonal partial least squares-discriminate analysis (OPLS-DA). Regarding gastrointestinal functions, d-gal significantly decreased the small intestine propulsion rates and prolonged gastrointestinal transit time. In addition, d-gal significantly increased the oxidative damages. PCA results showed that d-gal interrupted the metabolic profiles of endogenous small molecules in aging rats. Furthermore, OPLS-DA showed that 40 metabolites were screened and identified to be involved in the disruption of gastrointestinal functions in aging rats. Accordingly, seven metabolic pathways were recognized as the most influenced pathways associated with gastrointestinal functions of aging rats induced by d-gal, including amino acid metabolism, energy metabolism, intestinal flora metabolism, and metabolism of short chain fatty acids. It is the first report to investigate the effects and underlying mechanisms of d-gal on gastrointestinal functions of aging rats from the perspective of fecal metabolomics. The current results are conducive to further comprehensively understand d-gal-induced aging and will expand the applications of d-gal in pharmacological researches.

Influence of Drying Method on NMR-Based Metabolic Profiling of Human Cell Lines

Metabolic profiling of cell line and tissue extracts involves sample processing that includes a drying step prior to re-dissolving the cell or tissue extracts in a buffer for analysis by GC/LC-MS or NMR. Two of the most commonly used drying techniques are centrifugal evaporation under vacuum (SpeedVac) and lyophilization. Here, NMR spectroscopy was used to determine how the metabolic profiles of hydrophilic extracts of three human pancreatic cancer cell lines, MiaPaCa-2, Panc-1 and AsPC-1, were influenced by the choice of drying technique. In each of the three cell lines, 40-50 metabolites were identified as having statistically significant differences in abundance in redissolved extract samples depending on the drying technique used during sample preparation. In addition to these differences, some metabolites were only present in the lyophilized samples, for example, n-methyl-α-aminoisobutyric acid, n-methylnicotimamide, sarcosine and 3-hydroxyisovaleric acid, whereas some metabolites were only present in SpeedVac dried samples, for example, trimethylamine. This research demonstrates that the choice of drying technique used during the preparation of samples of human cell lines or tissue extracts can significantly influence the observed metabolome, making it important to carefully consider the selection of a drying method prior to preparation of such samples for metabolic profiling.

RANCM: a new ranking scheme for assigning confidence levels to metabolite assignments in NMR-based metabolomics studies

INTRODUCTION

The Metabolomics Standards Initiative has recommended four categories for metabolite assignments in NMR-based metabolic profiling studies. The "putatively annotated compound" category is most commonly reported by metabolomics investigators. However, there is significant ambiguity in reliability of "putatively annotated compound" assignments, which can range from low confidence made on minimal corroborating data to high confidence made on substantial corroborating data.

OBJECTIVES

To introduce a new ranking system, Rank and AssigN Confidence to Metabolites (RANCM), to assign confidence levels to "putatively annotated compound" assignments in NMR-based metabolic profiling studies.

METHODS

The ranking system was constructed with three confidence levels ranging from Rank 1 for the lowest confidence assignment level to Rank 3 for the highest confidence assignment level. A decision tree was constructed to guide rank selection for each metabolite assignment.

RESULTS

Examples are provided from experimental data demonstrating how to use the decision tree to make confidence level assignments to "putatively annotated compounds" in each of the three rank levels. A standard Excel sheet template is provided to facilitate decision-making, documentation and submission to data repositories.

CONCLUSION

RANCM is intended to reduce the ambiguity in "putatively annotated compound" assignments, to facilitate effective communication of the degree of confidence in "putatively annotated compound" assignments, and to make it easier for non-experts to evaluate the significance and reliability of NMR-based metabonomics studies. The system is straightforward to implement, based on the most common datasets collected in NMR-based metabolic profiling studies, and can be used with equal rigor and significance with any set of NMR datasets.

Spatial variations in gut permeability are linked to type 1 diabetes development in non-obese diabetic mice

OBJECTIVES

To determine if spatial variations in gut permeability play a role in regulating type 1 diabetes (T1D) progression.

RESEARCH DESIGN AND METHODS

Spatially resolved duodenum, jejunum, ileum, and large intestine sections from end-stage T1D non-obese diabetic (NOD) mice were probed by immunohistochemistry to quantify zonulin levels as a measure of gut permeability in early-progressor and late-progressor NOD mice in comparison with non-progressor NOD mice and healthy NOR/LtJ control mice.

RESULTS

Zonulin levels were elevated in the small and large intestines in early-progressor and late-progressor NOD mice in comparison with non-progressor NOD mice and healthy NOR control mice. In early-onset mice, elevated zonulin levels were maximum in the duodenum and jejunum and decreased in the ileum and large intestine. In late-progressor mice, zonulin levels were elevated almost evenly along the small and large intestines. In non-progressor NOD mice, zonulin levels were comparable with NOR control levels in both the small and large intestines.

CONCLUSIONS

Elevated zonulin expression levels indicated that gut permeability was increased both in the small and large intestines in NOD mice that progressed to end-stage T1D in comparison with non-progressor NOD mice and healthy NOR control mice. Highest elevations in zonulin levels were observed in the duodenum and jejunum followed by the ileum and large intestines. Spatial variations in gut permeability appeared to play a role in regulating the rate and severity of T1D progression in NOD mice indicating that spatial variations in gut permeability should be investigated as a potentially important factor in human T1D progression.