NMR-based metabolomics study of canine bladder cancer

Genome-wide analyses reveals an association between invasive urothelial carcinoma in the Shetland sheepdog and NIPAL1

Naturally occurring canine invasive urinary carcinoma (iUC) closely resembles human muscle invasive bladder cancer in terms of histopathology, metastases, response to therapy, and low survival rate. The heterogeneous nature of the disease has led to the association of large numbers of risk loci in humans, however most are of small effect. There exists a need for new and accurate animal models of invasive bladder cancer. In dogs, distinct breeds show markedly different rates of iUC, thus presenting an opportunity to identify additional risk factors and overcome the locus heterogeneity encountered in human mapping studies. In the association study presented here, inclusive of 100 Shetland sheepdogs and 58 dogs of other breeds, we identify a homozygous protein altering point mutation within the NIPAL1 gene which increases risk by eight-fold (OR = 8.42, CI = 3.12-22.71), accounting for nearly 30% of iUC risk in the Shetland sheepdog. Inclusion of six additional loci accounts for most of the disease risk in the breed and explains nearly 75% of the phenotypes in this study. When combined with sequence data from tumors, we show that variation in the MAPK signaling pathway is an overarching cause of iUC susceptibility in dogs.

Cancer evaluation in dogs using cerumen as a source for volatile biomarker prospection

Cancer is one of the deadliest diseases in humans and dogs. Nevertheless, most tumor types spread faster in canines, and early cancer detection methods are necessary to enhance animal survival. Here, cerumen (earwax) was tested as a source of potential biomarkers for cancer evaluation in dogs. Earwax samples from dogs were collected from tumor-bearing and clinically healthy dogs, followed by Headspace/Gas Chromatography-Mass Spectrometry (HS/GC-MS) analyses and multivariate statistical workflow. An evolutionary-based multivariate algorithm selected 18 out of 128 volatile metabolites as a potential cancer biomarker panel in dogs. The candidate biomarkers showed a full discrimination pattern between tumor-bearing dogs and cancer-free canines with high accuracy in the test dataset: an accuracy of 95.0% (75.1-99.9), and sensitivity and specificity of 100.0% and 92.9%, respectively. In summary, this work raises a new perspective on cancer diagnosis in dogs, being carried out painlessly and non-invasive, facilitating sample collection and periodic application in a veterinary routine.

Lyme Borreliosis in Dogs: Background, Epidemiology, Diagnostics, Treatment and Prevention

Lyme borreliosis (LB) is a multisystemic tick-borne disease that can affect many organs and have various clinical manifestations in dogs. We attempted to summarise various aspects of Lyme disease: i. e., pathogenesis, epidemiology, benefits and risks of diagnostic approaches, treatment options, and prevention in dogs. Several diagnostic bottlenecks for LB in dogs and humans are compared. Because the occurrence of LB in both humans and dogs is closely related, monitoring its prevalence in dogs as sentinel animals is an excellent aid in assessing the risk of Lyme disease in a given geographic area. Although clinical symptoms in humans help clinicians diagnose LB, they are ineffective in dogs because canines rarely exhibit LB symptoms. Despite significant differences in sensitivity and specificity, sero-logical two-step detection of antibodies against Borrelia spp. (ELISA and Western blot) is the most commonly used method in humans and dogs. The limitations of the assay highlight the need for further research to develop new clinical markers and more accurate diagnostic tests. Due to the lack of a specific all-encompassing LB test, a definitive diagnosis of LB remains a difficult and time-consuming process in human and veterinary medicine. Understanding the disease prevalence and diagnostics, as well as preventing its spread with effective and timely treatment, are fundamental principles of good disease management.

Monoisotopic silver nanoparticles-based mass spectrometry imaging of human bladder cancer tissue: Biomarker discovery

PURPOSE

Bladder cancer (BC) is the 10th most common form of cancer worldwide and the 2nd most common cancer of the urinary tract after prostate cancer, taking into account both incidence and prevalence.

MATERIALS/METHODS

Tissues from patients with BC and also tissue extracts were analyzed by laser desorption/ionization mass spectrometry imaging (LDI-MSI) with monoisotopic silver-109 nanoparticles-enhanced target (¹⁰⁹AgNPET).

RESULTS

Univariate and multivariate statistical analyses revealed 10 metabolites that differentiated between tumor and normal tissues from six patients with diagnosed BC. Selected metabolites are discussed in detail in relation to their mass spectrometry (MS) imaging results. The pathway analysis enabled us to link these compounds with 17 metabolic pathways.

CONCLUSIONS

According to receiver operating characteristic (ROC) analysis of biomarkers, 10 known metabolites were identified as the new potential biomarkers with areas under the curve (AUC) higher than >0.99. In both univariate and multivariate analysis, it was predicted that these compounds could serve as useful discriminators of cancerous versus normal tissue in patients diagnosed with BC.

Exploration of urinary metabolite dynamicity for early detection of pregnancy in water buffaloes

Early and precise pregnancy diagnosis can reduce the calving interval by minimizing postpartum period. The present study explored the differential urinary metabolites between pregnant and non-pregnant Murrah buffaloes (Bubalus bubalis) during early gestation to identify potential pregnancy detection biomarkers. Urine samples were collected on day 0, 10, 18, 35 and 42 of gestation from the pregnant (n = 6) and on day 0, 10 and 18 post-insemination from the non-pregnant (n = 6) animals. ¹H-NMR-based untargeted metabolomics followed by multivariate analysis initially identified twenty-four differentially expressed metabolites, among them 3-Hydroxykynurenine, Anthranilate, Tyrosine and 5-Hydroxytryptophan depicted consistent trends and matched the selection criteria of potential biomarkers. Predictive ability of these individual biomarkers through ROC curve analyses yielded AUC values of 0.6–0.8. Subsequently, a logistic regression model was constructed using the most suitable metabolite combination to improve diagnostic accuracy. The combination of Anthranilate, 3-Hydroxykynurenine, and Tyrosine yielded the best AUC value of 0.804. Aromatic amino acid biosynthesis, Tryptophan metabolism, Phenylalanine and Tyrosine metabolism were identified as potential pathway modulations during early gestation. The identified biomarkers were either precursors or products of these metabolic pathways, thus justifying their relevance. The study facilitates precise non-invassive urinary metabolite-based pen-side early pregnancy diagnostics in buffaloes, eminently before 21 days post-insemination.

The Novel Diagnostic Techniques and Biomarkers of Canine Mammary Tumors

Canine mammary tumors (CMTs) are considered a serious clinical problem in older bitches. Due to the high malignancy rate and poor prognosis, an early diagnosis is essential. This article is a summary of novel diagnostic techniques as well as the main biomarkers of CMTs. So far, CMTs are detected only when changes in mammary glands are clinically visible and surgical removal of the mass is the only recommended treatment. Proper diagnostics of CMT is especially important as they represent a very diverse group of tumors and therefore different treatment approaches may be required. Recently, new diagnostic options appeared, like a new cytological grading system of CMTs or B-mode ultrasound, the Doppler technique, contrast-enhanced ultrasound, and real-time elastography, which may be useful in pre-surgical evaluation. However, in order to detect malignancies before macroscopic changes are visible, evaluation of serum and tissue biomarkers should be considered. Among them, we distinguish markers of the cell cycle, proliferation, apoptosis, metastatic potential and prognosis, hormone receptors, inflammatory and more recent: metabolomic, gene expression, miRNA, and transcriptome sequencing markers. The use of a couple of the above-mentioned markers together seems to be the most useful for the early diagnosis of neoplastic diseases as well as to evaluate response to treatment, presence of tumor progression, or further prognosis. Molecular aspects of tumors seem to be crucial for proper understanding of tumorigenesis and the application of individual treatment options.

Metabolomic Approaches for Detection and Identification of Biomarkers and Altered Pathways in Bladder Cancer

Metabolomic analysis has proven to be a useful tool in biomarker discovery and the molecular classification of cancers. In order to find new biomarkers, and to better understand its pathological behavior, bladder cancer also has been studied using a metabolomics approach. In this article, we review the literature on metabolomic studies of bladder cancer, focusing on the different available samples (urine, blood, tissue samples) used to perform the studies and their relative findings. Moreover, the multi-omic approach in bladder cancer research has found novel insights into its metabolic behavior, providing excellent start-points for new diagnostic and therapeutic strategies. Metabolomics data analysis can lead to the discovery of a “signature pathway” associated with the progression of bladder cancer; this aspect could be potentially valuable in predictions of clinical outcomes and the introduction of new treatments. However, further studies are needed to give stronger evidence and to make these tools feasible for use in clinical practice.

Molecular Markers in Urinary Bladder Cancer: Applications for Diagnosis, Prognosis and Therapy

Cancer of the urinary bladder is a neoplasm with considerable importance in veterinary medicine, given its high incidence in several domestic animal species and its life-threatening character. Bladder cancer in companion animals shows a complex and still poorly understood biopathology, and this lack of knowledge has limited therapeutic progress over the years. Even so, important advances concerning the identification of tumour markers with clinical applications at the diagnosis, prognosis and therapeutic levels have recently been made, for example, the identification of pathological BRAF mutations. Those advances are now facilitating the introduction of targeted therapies. The present review will address such advances, focusing on small animal oncology and providing the reader with an update on this field. When appropriate, comparisons will be drawn with bladder cancer in human patients, as well as with experimental models of the disease.

Untargeted Metabolomics Identify a Panel of Urinary Biomarkers for the Diagnosis of Urothelial Carcinoma of the Bladder, as Compared to Urolithiasis with or without Urinary Tract Infection in Dogs

Urothelial carcinoma (UC), the most common urologic cancer in dogs, is often diagnosed late because the clinical signs are shared by other non-malignant lower urinary tract disorders (LUTD). The urine-based BRAFV595E test for UC is highly effective only in certain breeds; hence additional non-invasive biomarkers of UC are needed. Here, urine from dogs with UC (n = 27), urolithiasis (n = 8), or urolithiasis with urinary tract infection (UTI) (n = 8) were subjected to untargeted metabolomics analyses, using GC-TOF-MS for primary metabolites, QTOF-MS for complex lipids, and HILIC-QTOF MS for secondary and charged metabolites. After adjusting for age and sex, we identified 1123 known metabolites that were differentially expressed between UC and LUTD. Twenty-seven metabolites were significant (1.5 ≤ log2FC ≤ −1.5, adjusted p-value < 0.05); however, 10 of these could be attributed to treatment-related changes. Of the remaining 17, 6 (hippuric acid, N-Acetylphenylalanine, sarcosine, octanoylcarnitine, N-alpha-methylhistamine, glycerol-3-galactoside) discriminated between UC and LUTD (area under the ROC curve > 0.85). Of the 6 metabolites, only hippuric acid and N-alpha-methylhistamine were discriminatory in both male (n = 20) and female (n = 23) dogs, while sarcosine was an effective discriminator in several breeds, but only in females. Further investigation of these metabolites is warranted for potential use as non-invasive diagnostic biomarkers of dogs with UC that present with LUTD-related clinical signs.

Multi Platforms Strategies and Metabolomics Approaches for the Investigation of Comprehensive Metabolite Profile in Dogs with Babesia canis Infection

Canine babesiosis is an important tick-borne disease worldwide, caused by parasites of the Babesia genus. Although the disease process primarily affects erythrocytes, it may also have multisystemic consequences. The goal of this study was to explore and characterize the serum metabolome, by identifying potential metabolites and metabolic pathways in dogs naturally infected with Babesia canis using liquid and gas chromatography coupled to mass spectrometry. The study included 12 dogs naturally infected with B. canis and 12 healthy dogs. By combining three different analytical platforms using untargeted and targeted approaches, 295 metabolites were detected. The untargeted ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) metabolomics approach identified 64 metabolites, the targeted UHPLC-MS/MS metabolomics approach identified 205 metabolites, and the GC-MS metabolomics approach identified 26 metabolites. Biological functions of differentially abundant metabolites indicate the involvement of various pathways in canine babesiosis including the following: glutathione metabolism; alanine, aspartate, and glutamate metabolism; glyoxylate and dicarboxylate metabolism; cysteine and methionine metabolism; and phenylalanine, tyrosine, and tryptophan biosynthesis. This study confirmed that host–pathogen interactions could be studied by metabolomics to assess chemical changes in the host, such that the differences in serum metabolome between dogs with B. canis infection and healthy dogs can be detected with liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) methods. Our study provides novel insight into pathophysiological mechanisms of B. canis infection.

Preliminary demonstration of benchtop NMR metabolic profiling of feline urine: chronic kidney disease as a case study

Objective

The use of benchtop metabolic profiling technology based on nuclear magnetic resonance (NMR) was evaluated in a small cohort of cats with a view to applying this as a viable and rapid metabolic tool to support clinical decision making.

Results

Urinary metabolites were analysed from four subjects consisting of two healthy controls and two chronic kidney disease (CKD) IRIS stage 2 cases. The study identified 15 metabolites in cats with CKD that were different from the controls. Among them were acetate, creatinine, citrate, taurine, glycine, serine and threonine. Benchtop NMR technology is capable of distinguishing between chronic kidney disease case and control samples in a pilot feline cohort based on metabolic profile. We offer perspectives on the further development of this pilot work and the potential of the technology, when combined with sample databases and computational intelligence techniques to offer a clinical decision support tool not only for cases of renal disease but other metabolic conditions in the future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-021-05888-y.

NMR metabolomic and microarray-based transcriptomic data integration identifies unique molecular signatures of hypersensitivity pneumonitis

Hypersensitivity pneumonitis (HP) is an immune-mediated granulomatous interstitial lung disease (ILD) that results from repeated inhalation of certain antigens. Despite major advances in research, pathophysiology of the disease remains poorly understood. The present study combines metabolomic and transcriptomic data to determine alterations in HP subjects as compared with healthy controls. Metabolic signatures were identified in serum, exhaled breath condensate (EBC) and bronchoalveolar lavage fluid (BALF) of HP patients using proton nuclear magnetic resonance (NMR) metabolomics. The expression of three metabolites, i.e., lactate, pyruvate, and proline, was found to be significantly altered in all three biofluids. The potential of differential diagnosis based on these three metabolites was investigated by including a group of patients with sarcoidosis, which is another type of granulomatous ILD. In addition, differentially expressed transcriptomic fingerprints in blood samples were identified by analyzing a Gene Expression Omnibus (GEO) database. The transcriptomics analysis of these microarray-based data revealed 59 genes to be significantly dysregulated in patients with HP. Over representation analysis of the metabolites and genes of interest was performed using IMPaLA (Integrated Molecular Pathway Level Analysis) version 12. Integrated analysis of serum metabolite signatures and blood gene expression suggests dysregulation of PI3K-AKT signaling and TCA cycle pathways in these patients. This preliminary study is a step towards better understanding of the pathogenesis of HP by identification of differentially expressed metabolites and transcriptomic fingerprints. These molecular signatures may be explored as diagnostic markers for differentiating HP from other lung diseases.

Comparative Cancer Cell Signaling in Muscle-Invasive Urothelial Carcinoma of the Bladder in Dogs and Humans

Muscle-invasive urothelial carcinoma (MIUC) is the most common type of bladder malignancy in humans, but also in dogs that represent a naturally occurring model for this disease. Dogs are immunocompetent animals that share risk factors, pathophysiological features, clinical signs and response to chemotherapeutics with human cancer patients. This review summarizes the fundamental pathways for canine MIUC initiation, progression, and metastasis, emerging therapeutic targets and mechanisms of drug resistance, and proposes new opportunities for potential prognostic and diagnostic biomarkers and therapeutics. Identifying similarities and differences between cancer signaling in dogs and humans is of utmost importance for the efficient translation of in vitro research to successful clinical trials for both species.

The Clinical Experiences of Urine Metabolomics of Genitourinary Urothelial Cancer in a Tertiary Hospital in Taiwan

Few studies have addressed the impact of diagnostic urine metabolites and the clinical outcomes associated with genitourinary urothelial (GU) cancer to date. Furthermore, longitudinal analysis of the dynamics of urine metabolites contributing to the detection of GU cancer has not yet been fully investigated; therefore, the discovery of novel diagnostic urine biomarkers is of enormous interest. We explored the correlation of the urine metabolomic profiles to GU cancers. The aqueous metabolites of the GU cancer and the control were also identified and analyzed through high-resolution1H nuclear magnetic resonance (NMR) spectroscopy. Compared with the control, the urine metabolites of the tumor were studied in relation to changes over time in a linear mixed model for repeated measures. The urine metabolites of sixty-three (44 male and 19 female) patients with GU cancers were systemically analyzed. The urine metabolite profile in GU cancer was significantly higher than those in the control group (p<0.05). Sevenurine metabolites including histidine, propylene glycol, valine, leucine, acetylsalicylate, glycine, and isoleucine as well as other pathways were identified statistically and were significantly associated with GU cancer detection with longitudinal analysis. We discovered that histidine, propylene glycol, valine, leucine, acetylsalicylate, glycine, isoleucine, succinic acid, lysine2-aminobutyric acid, and acetic acid are involved significantly in all types of male patients in whom the type (upper tract) of urine metabolites were found to be statistically significant compared with the control. We did not find any statistical significance in urine biomarkers between female and male patients. However, a statistically insignificant correlation was found among the grade and stage with the metabolites.

Indication of high lipid content in epithelial-mesenchymal transitions of breast tissues

The epithelial-mesenchymal transition (EMT) is a crucial process in cancer progression and metastasis. Study of metabolic changes during the EMT process is important in seeking to understand the biochemical changes associated with cancer progression, not least in scoping for therapeutic strategies aimed at targeting EMT. Due to the potential for high sensitivity and specificity, Raman spectroscopy was used here to study the metabolic changes associated with EMT in human breast cancer tissue. For Raman spectroscopy measurements, tissue from 23 patients were collected, comprising non-lesional, EMT and non-EMT formalin-fixed and paraffin embedded breast cancer samples. Analysis was made in the fingerprint Raman spectra region (600-1800 cm-1) best associated with cancer progression biochemical changes in lipid, protein and nucleic acids. The ANOVA test followed by the Tukey's multiple comparisons test were conducted to see if there existed differences between non-lesional, EMT and non-EMT breast tissue for Raman spectroscopy measurements. Results revealed that significant differences were evident in terms of intensity between the non-lesional and EMT samples, as well as the EMT and non-EMT samples. Multivariate analysis involving independent component analysis, Principal component analysis and non-negative least square were used to analyse the Raman spectra data. The results show significant differences between EMT and non-EMT cancers in lipid, protein, and nucleic acids. This study demonstrated the capability of Raman spectroscopy supported by multivariate analysis in analysing metabolic changes in EMT breast cancer tissue.

Novel Metabolic Signatures of Prostate Cancer Revealed by 1H-NMR Metabolomics of Urine

Prostate cancer (PC) is one of the most common male cancers worldwide. Until now, there is no consensus about using urinary metabolomic profiling as novel biomarkers to identify PC. In this study, urine samples from 50 PC patients and 50 non-cancerous individuals (control group) were collected. Based on 1H nuclear magnetic resonance (1H-NMR) analysis, 20 metabolites were identified. Subsequently, principal component analysis (PCA), partial least squares-differential analysis (PLS-DA) and ortho-PLS-DA (OPLS-DA) were applied to find metabolites to distinguish PC from the control group. Furthermore, Wilcoxon test was used to find significant differences between the two groups in metabolite urine levels. Guanidinoacetate, phenylacetylglycine, and glycine were significantly increased in PC, while L-lactate and L-alanine were significantly decreased. The receiver operating characteristics (ROC) analysis revealed that the combination of guanidinoacetate, phenylacetylglycine, and glycine was able to accurately differentiate 77% of the PC patients with sensitivity = 80% and a specificity = 64%. In addition, those three metabolites showed significant differences in patients stratified for Gleason score 6 and Gleason score ≥7, indicating potential use to detect significant prostate cancer. Pathway enrichment analysis using the KEGG (Kyoto Encyclopedia of Genes and Genomes) and the SMPDB (The Small Molecule Pathway Database) revealed potential involvement of KEGG "Glycine, Serine, and Threonine metabolism" in PC. The present study highlights that guanidinoacetate, phenylacetylglycine, and glycine are potential candidate biomarkers of PC. To the best knowledge of the authors, this is the first study identifying guanidinoacetate, and phenylacetylglycine as potential novel biomarkers in PC.

Metabolic Changes in Serum Metabolome of Beagle Dogs Fed Black Ginseng

The effects of black ginseng, which has many kinds of biological activities, on dogs was investigated. Serum samples of beagle dogs, which were fed with black ginseng for 8 weeks, were measured using high-resolution magic angle spinning (HR-MAS) nuclear magnetic resonance (NMR) spectrometry. Acquired NMR data from the serum of dogs fed for 0, 4, and 8 weeks were analyzed by metabolic profiling and multivariate statistical analysis. In statistical analysis and biomarker analysis results of metabolite profiles, formate, glutamine, histidine, isoleucine, leucine, proline, and valine had variable importance in projection (VIP) scores above 1.0 and excellent area under the curve (AUC) values of receiver operating characteristic (ROC) curves above 0.9. In the result of multivariate statistical analysis, the score plot showed the discrimination between before and after feeding of black ginseng. These differences in metabolic profiles are considered to be due to the involvement of metabolic processes following black ginseng administration, such as enhancing immunity and energy metabolism. Through metabolomics analysis, we confirmed the biological efficacy of black ginseng in dogs and also confirmed that metabolomics can be applied to the pet health industry.

Metabolomics in the study of spontaneous animal diseases

Using analytical chemistry techniques such as nuclear magnetic resonance (NMR) spectroscopy and liquid or gas chromatography-mass spectrometry (LC/GC-MS), metabolomics allows detection of most endogenous and exogenous metabolites in a biological sample. Metabolomics has a wide range of applications, and has been employed in nutrition science, toxicology, environmental studies, and systems biology. Metabolomics is particularly useful in biomedical science, and has been used for diagnostic laboratory testing, identifying targets for drug development, and monitoring drug metabolism, mode of action, and toxicity. Despite its immense potential, metabolomics remains underutilized in the study of spontaneous animal diseases. Our aim was to comprehensively review the existing literature on the use of metabolomics in spontaneous veterinary diseases. Three databases were used to find journal articles that applied metabolomics in veterinary medicine. A screening process was then conducted to eliminate references that did not meet the eligibility criteria; only primary research studies investigating spontaneous animal disease were included; 38 studies met the inclusion criteria. The main techniques used were NMR and MS. All studies detected metabolite alterations in diseased animals compared with non-diseased animals. Metabolomics was mainly used to study diseases of the digestive, reproductive, and musculoskeletal systems. Inflammatory conditions made up the largest proportion of studies when articles were categorized by disease process. Following a comprehensive analysis of the literature on metabolomics in spontaneous veterinary diseases, we concluded that metabolomics, although in its early stages in veterinary research, is a promising tool regarding diagnosis, biomarker discovery, and in uncovering new insights into disease pathophysiology.

Treatment With Hydrolyzed Diet Supplemented With Prebiotics and Glycosaminoglycans Alters Lipid Metabolism in Canine Inflammatory Bowel Disease

Canine inflammatory bowel disease (IBD) is a chronic, immunologically mediated intestinal disorder, resulting from the complex interaction of genetic, environmental and immune factors. Hydrolyzed diets are used in dogs with food-responsive diarrhea (FRD) to reduce adverse responses to immunostimulatory proteins. Prebiotics (PRBs) and glycosaminoglycans (GAGs) have previously been demonstrated to show anti-inflammatory activity in the intestinal mucosa. Notably, hydrolyzed diets combined with the administration of PRBs and GAGs offer a promising approach for the treatment of canine IBD. Our aim was to investigate the effects of hydrolyzed diet and GAG+PRB co-treatment on the serum metabolomic profile of IBD dogs. Dogs with IBD randomly received either hydrolyzed diet supplemented with GAGs and PRBs (treatment 1) or hydrolyzed diet alone (treatment 2) for 10 weeks. A targeted metabolomics approach using mass spectrometry was performed to quantify changes in the serum metabolome before and after treatment and between treatment 1 and 2. Principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), hierarchical cluster analysis (HCA) and univariate statistics were used to identify differences between the treatment groups. PCA, PLS-DA, and HCA showed a clear clustering of IBD dogs before and after hydrolyzed diet, indicating that the treatment impacted the serum metabolome. Univariate analysis revealed that most of the altered metabolites were involved in lipid metabolism. The most impacted lipid classes were components of cell membranes, including glycerophospholipids, sphingolipids, and di- and triglycerides. In addition, changes in serum metabolites after GAG+PRB co-treatment suggested a possible additional beneficial effect on the lipid metabolism in IBD dogs. In conclusion, the present study showed a significant increase in metabolites that protect gut cell membrane integrity in response to hydrolyzed diet alone or in combination with GAG+PRB co-treatment. Administration of such treatment over 70 days improved selected serum biomarkers of canine IBD, possibly indicating improved intestinal membrane integrity.

NMR-derived targeted serum metabolic biomarkers appraisal of bladder cancer: A pre- and post-operative evaluation

With high morbidity and mortality, urinary bladder cancer (BC) ranks fifth among common cancers globally. The inherent limitations of urine cytology and cystoscopy, and marginal enhancements in the rate of survival promt us to develop surrogate serum based metabolic biomarkers of screening, identification, and follow-up protocols of management for BC patients. Earlier, we exhibited that abnormal expression levels of dimethylamine (DMA), malonate, lactate, glutamine, histidine, and valine in serum may be used as signature metabolites to differentiate BC from healthy controls (HC) (J. Proteome Res. 2013; 12(12):5839-50). Here we further gauge and validate these observations by comparing pre-operative to post-operative follow-up BC patients. This study was conducted on 160 sera samples involving HC (n = 52), pre-operative (n = 55) and post-operative (n = 53) BC cases. ¹H nuclear magnetic resonance (NMR) spectroscopy was used to generate serum metabolic profiles and to gauge aberrantly expressed metabolites. The targeted metabolomic approach revealed that the expression levels of these signature metabolites were progressively and significantly decreased in post-operative follow-up at the interval of 30, 60, and 90 days compared to pre-operative BC sera samples and were maintained at HC levels. Serum metabolic biomarkers appear to be an inspiring and least-invasive tactic for detection and prognosticating BC patient follow-up.

Urinary proteome and metabolome in dogs (Canis lupus familiaris): The effect of chronic kidney disease

Chronic kidney disease (CKD) is a progressive and irreversible disease. Although urine is an ideal biological sample for proteomics and metabolomics studies, sensitive and specific biomarkers are currently lacking in dogs. This study characterised dog urine proteome and metabolome aiming to identify and possibly quantify putative biomarkers of CKD in dogs. Twenty-two healthy dogs and 28 dogs with spontaneous CKD were selected and urine samples were collected. Urinary proteome was separated by SDS-PAGE and analysed by mass spectrometry, while urinary metabolome was analysed in protein-depleted samples by 1D ¹H NMR spectra. The most abundant proteins in urine samples from healthy dogs were uromodulin, albumin and, in entire male dogs, arginine esterase. In urine samples from CKD dogs, the concentrations of uromodulin and albumin were significantly lower and higher, respectively, than in healthy dogs. In addition, these samples were characterised by a more complex protein pattern indicating mixed glomerular (protein bands ≥65 kDa) and tubular (protein bands <65 kDa) proteinuria. Urine spectra acquired by NMR allowed the identification of 86 metabolites in healthy dogs, belonging to 49 different pathways mainly involved in amino acid metabolism, purine and aminoacyl-tRNA biosynthesis or tricarboxylic acid cycle. Seventeen metabolites showed significantly different concentrations when comparing healthy and CKD dogs. In particular, carnosine, trigonelline, and cis-aconitate, might be suggested as putative biomarkers of CKD in dogs. SIGNIFICANCE: Urine is an ideal biological sample, however few proteomics and metabolomics studies investigated this fluid in dogs and in the context of CKD (chronic kidney disease). In this research, applying a multi-omics approach, new insights were gained regarding the molecular changes triggered by this disease in canine urinary proteome and metabolome. In particular, the involvement of the tubular component was highlighted, suggesting uromodulin, trigonelline and carnosine as possible biomarkers of CKD in dogs.

Untargeted Tumor Metabolomics with Liquid Chromatography-Surface-Enhanced Raman Spectroscopy

Metabolomics is a powerful systems biology approach that monitors changes in biomolecule concentrations to diagnose and monitor health and disease. However, leading metabolomics technologies, such as NMR and mass spectrometry (MS), access only a small portion of the metabolome. Now an approach is presented that uses the high sensitivity and chemical specificity of surface-enhanced Raman scattering (SERS) for online detection of metabolites from tumor lysates following liquid chromatography (LC). The results demonstrate that this LC-SERS approach has metabolite detection capabilities comparable to the state-of-art LC-MS but suggest a selectivity for the detection of a different subset of metabolites. Analysis of replicate LC-SERS experiments exhibit reproducible metabolite patterns that can be converted into barcodes, which can differentiate different tumor models. Our work demonstrates the potential of LC-SERS technology for metabolomics-based diagnosis and treatment of cancer.

Canine metabolomics advances

INTRODUCTION

Canis lupus familiaris is a domestic dog and many owners consider their pets as a family member. Medical bills with dogs are overcame only by the health care received by humans. Medical care is constantly progressing, and so is veterinary care. Metabolomics is the ''omic" technique aimed to the study of metabolome, low-molecular weight molecules, through biofluids or tissue samples. And it also allows to evaluate disease diagnosis and prognosis, therapeutic evaluation and toxicological studies.

OBJECTIVES

The goal of this paper is to review the current and potential applications of metabolomics in domestic dogs.

METHOD

ScienceDirect, Scopus, Reaxys and PubMed were searched for papers that performed canine metabolomics in any research area.

RESULTS

We analysed 38 papers, published until April 2019 in canine metabolomics approach. Metabolomic research in dogs so far can be divided into three areas: (a) Metabolomics studies in veterinary science, such as improving pet dogs health and welfare. (b) Diet, breeds and species discrimination. (c) Use of dogs as animal model in different diseases and drug development (evaluation toxicity and effect).

CONCLUSIONS

The results of this review showed that interest in metabolomics is growing in veterinary research. Several canine diseases have been evaluated with some promise for potential biomarker and/or disease mechanism discovery. Because canine metabolomics is a relatively new area, the researches spread across different research areas and with few studies in each area.

Genome-wide association studies of 74 plasma metabolites of German shepherd dogs reveal two metabolites associated with genes encoding their enzymes

INTRODUCTION

German shepherd dogs (GSDs) are a popular breed affected by numerous disorders. Few studies have explored genetic variations that influence canine blood metabolite levels.

OBJECTIVES

To investigate genetic variants affecting the natural metabolite variation in GSDs.

METHODS

A total of 82 healthy GSDs were genotyped on the Illumina CanineHD Beadchip, assaying 173,650 markers. For each dog, 74 metabolites were measured through liquid and gas chromatography mass spectrometry (LC-MS and GC-MS) and were used as phenotypes for genome-wide association analyses (GWAS). Sliding window and homozygosity analyses were conducted to fine-map regions of interest, and to identify haplotypes and gene dosage effects.

RESULTS

Summary statistics for 74 metabolites in this population of GSDs are reported. Forty-one metabolites had significant associations at a false discovery rate of 0.05. Two associations were located around genes which encode for enzymes for the relevant metabolites: 4-hydroxyproline was significantly associated to D-amino acid oxidase (DAO), and threonine to L-threonine 3-dehydrogenase (LOC477365). Three of the top ten haplotypes associated to 4-hydroxyproline included at least one SNP on DAO. These haplotypes occurred only in dogs with the highest 15 measurements of 4-hydroxyproline, ranging in frequency from 16.67 to 20%. None of the dogs were homozygous for these haplotypes. The top two haplotypes associated to threonine included SNPs on LOC477365 and were also overrepresented in dogs with the highest 15 measurements of threonine. These haplotypes occurred at a frequency of 90%, with 80% of these dogs homozygous for the haplotypes. In dogs with the lowest 15 measurements of threonine, the haplotypes occurred at a frequency of 26.67% and 0% homozygosity.

CONCLUSION

DAO and LOC477365 were identified as candidate genes affecting the natural plasma concentration of 4-hydroxyproline and threonine, respectively. Further investigations are needed to validate the effects of the variants on these genes.

Recent advances in the metabolomic study of bladder cancer

INTRODUCTION

Metabolomics is a chemical process, involving the characterization of metabolites and cellular metabolism. Recent studies indicate that numerous metabolic pathways are altered in bladder cancer (BLCA), providing potential targets for improved detection and possible therapeutic intervention. We review recent advances in metabolomics related to BLCA and identify various metabolites that may serve as potential biomarkers for BLCA. Areas covered: In this review, we describe the latest advances in defining the BLCA metabolome and discuss the possible clinical utility of metabolic alterations in BLCA tissues, serum, and urine. In addition, we focus on the metabolic alterations associated with tobacco smoke and racial disparity in BLCA. Expert commentary: Metabolomics is a powerful tool which can shed new light on BLCA development and behavior. Key metabolites may serve as possible markers of BLCA. However, prospective validation will be needed to incorporate these markers into clinical care.

Urologic Oncology

Primary renal tumors are an uncommon diagnosis in small animals. Presentation, treatment, and prognosis depend on tumor type. Surgery with or without chemotherapy are the mainstays of treatment. Transitional cell carcinoma is the most common tumor of the urinary system. Clinical signs include hematuria, stranguria, and pollakiuria. Metastatic disease can develop over time within medial iliac lymph nodes, lungs, and vertebrae. Treatment of transitional cell carcinoma centers on chemotherapy with mitoxantrone, vinblastine, or carboplatin. Other agents used with success, include toceranib phosphate and chlorambucil. Interventional surgery, such as stenting and laser ablation, is used in a palliative setting addressing urinary obstruction.

Nuclear magnetic resonance spectroscopy as a new approach for improvement of early diagnosis and risk stratification of prostate cancer

Prostate cancer (PCa) is the second most common male cancer worldwide and the fifth leading cause of death from cancer in men. Early detection and risk stratification is the most effective way to improve the survival of PCa patients. Current PCa biomarkers lack sufficient sensitivity and specificity to cancer. Metabolite biomarkers are evolving as a new diagnostic tool. This review is aimed to evaluate the potential of metabolite biomarkers for early detection, risk assessment, and monitoring of PCa. Of the 154 identified publications, 27 and 38 were original papers on urine and serum metabolomics, respectively. Nuclear magnetic resonance (NMR) is a promising method for measuring concentrations of metabolites in complex samples with good reproducibility, high sensitivity, and simple sample processing. Especially urine-based NMR metabolomics has the potential to be a cost-efficient method for the early detection of PCa, risk stratification, and monitoring treatment efficacy.

Application of post-genomic techniques in dog cancer research

Omics techniques have been widely applied to veterinary science, although mostly on farm animal productions and infectious diseases. In canine oncology, on the contrary, the use of omics methodologies is still far behind. This review presents the most recent achievement in the application of postgenomic techniques, such as transcriptomics, proteomics, and metabolomics, to canine cancer research. The protocols to recover material suitable for omics analyses from formalin-fixed, paraffin-embedded tissues are presented, and omics applications for biomarker discovery and their potential for cancer diagnostics in veterinary medicine are highlighted.

Diagnostic performance of the urinary canine calgranulins in dogs with lower urinary or urogenital tract carcinoma

BACKGROUND

Onset of canine transitional cell carcinoma (TCC) and prostatic carcinoma (PCA) is usually insidious with dogs presenting at an advanced stage of the disease. A biomarker that can facilitate early detection of TCC/PCA and improve patient survival would be useful. S100A8/A9 (calgranulin A/B or calprotectin) and S100A12 (calgranulin C) are expressed by cells of the innate immune system and are associated with several inflammatory disorders. S100A8/A9 is also expressed by epithelial cells after malignant transformation and is involved in the regulation of cell proliferation and metastasis. S100A8/A9 is up-regulated in human PCA and TCC, whereas the results for S100A12 have been ambiguous. Also, the urine S100A8/A9-to-S100A12 ratio (uCalR) may have potential as a marker for canine TCC/PCA. Aim of the study was to evaluate the diagnostic accuracy of the urinary S100/calgranulins to detect TCC/PCA in dogs by using data and urine samples from 164 dogs with TCC/PCA, non-neoplastic urinary tract disease, other neoplasms, or urinary tract infections, and 75 healthy controls (nested case-control study). Urine S100A8/A9 and S100A12 (measured by species-specific radioimmunoassays and normalized against urine specific gravity [S100A8/A9_USG; S100A12_USG], urine creatinine concentration, and urine protein concentration and the uCalR were compared among the groups of dogs.

RESULTS

S100A8/A9_USG had the highest sensitivity (96%) and specificity (66%) to detect TCC/PCA, with specificity reaching 75% after excluding dogs with a urinary tract infection. The uCalR best distinguished dogs with TCC/PCA from dogs with a urinary tract infection (sensitivity: 91%, specificity: 60%). Using a S100A8/A9_USG ≥ 109.9 to screen dogs ≥6 years of age for TCC/PCA yielded a negative predictive value of 100%.

CONCLUSIONS

S100A8/A9_USG and uCalR may have utility for diagnosing TCC/PCA in dogs, and S100A8/A9_USG may be a good screening test for canine TCC/PCA.

Naturally Occurring Canine Invasive Urinary Bladder Cancer: A Complementary Animal Model to Improve the Success Rate in Human Clinical Trials of New Cancer Drugs

Genomic analyses are defining numerous new targets for cancer therapy. Therapies aimed at specific genetic and epigenetic targets in cancer cells as well as expanded development of immunotherapies are placing increased demands on animal models. Traditional experimental models do not possess the collective features (cancer heterogeneity, molecular complexity, invasion, metastasis, and immune cell response) critical to predict success or failure of emerging therapies in humans. There is growing evidence, however, that dogs with specific forms of naturally occurring cancer can serve as highly relevant animal models to complement traditional models. Invasive urinary bladder cancer (invasive urothelial carcinoma (InvUC)) in dogs, for example, closely mimics the cancer in humans in pathology, molecular features, biological behavior including sites and frequency of distant metastasis, and response to chemotherapy. Genomic analyses are defining further intriguing similarities between InvUC in dogs and that in humans. Multiple canine clinical trials have been completed, and others are in progress with the aim of translating important findings into humans to increase the success rate of human trials, as well as helping pet dogs. Examples of successful targeted therapy studies and the challenges to be met to fully utilize naturally occurring dog models of cancer will be reviewed.

Feline urine metabolomic signature: characterization of low-molecular-weight substances in urine from domestic cats

Objectives This aim of this study was to characterize the composition and content of the feline urine metabolome. Methods Eight healthy domestic cats were acclimated at least 10 days before starting the study. Urine samples (~2 ml) were collected by ultrasound-guided cystocentesis. Samples were centrifuged at 1000 × g for 8 mins, and the supernatant was analyzed by gas chromatography/time-of-flight mass spectrometery. The urine metabolome was characterized using an untargeted metabolomics approach. Results Three hundred and eighteen metabolites were detected in the urine of the eight cats. These molecules are key components of at least 100 metabolic pathways. Feline urine appears to be dominated by carbohydrates, carbohydrate conjugates, organic acid and derivatives, and amino acids and analogs. The five most abundant molecules were phenaceturic acid, hippuric acid, pseudouridine phosphate and 3-(4-hydroxyphenyl) propionic acid. Conclusions and relevance This study is the first to characterize the feline urine metabolome. The results of this study revealed the presence of multiple low-molecular-weight substances that were not known to be present in feline urine. As expected, the origin of the metabolites detected in urine was diverse, including endogenous compounds and molecules biosynthesized by microbes. Also, the diet seemed to have had a relevant role on the urine metabolome. Further exploration of the urine metabolic phenotype will open a window for discovering unknown, or poorly understood, metabolic pathways. In turn, this will advance our understanding of feline biology and lead to new insights in feline physiology, nutrition and medicine.

Amniotic fluid metabolomics and biochemistry analysis provides novel insights into the diet-regulated foetal growth in a pig model

Foetal loss and intrauterine growth restriction are major problems in mammals, but there are few effective ways in preventing it. Intriguingly, chitosan oligosaccharide (COS), a biomaterial derived from chitosan, can promote foetal survival and growth. Therefore, we have investigated how COS affects foetal survival and growth in a pig model. Fifty-two sows were divided into two treatment groups (n = 26) and fed either solely a control diet or a control diet that includes 100 mg/kg COS. Amniotic fluid and foetus samples from six sows that were of average body weight in each group were collected on gestation day 35. We applied a ¹H NMR-based metabolomics approach combined with biochemistry analysis to track the changes that occurred in the amniotic fluid of pregnant sows after COS intervention. Maternal COS inclusion had enhanced (P < 0.05) the foetal survival rate and size at 35 days. COS supplementation had both increased (P < 0.05) SOD, CAT and T-AOC activities and elevated (P < 0.05) IL-10, IgG and IgM concentrations in the amniotic fluid. Moreover, COS had affected (P < 0.05) the amniotic fluid’s lysine, citrate, glucose and hypoxanthine levels. Overall, COS inclusion induced amniotic fluid antioxidant status and metabolic profiles modifications characterising improvements in foetal survival and growth in a pig model.

Nuclear Magnetic Resonance technique in tumor metabolism

Cancer is one of the most serious diseases that cause an enormous number of deaths all over the world. Tumor metabolism has great discrimination from that of normal tissues. Exploring the tumor metabolism may be one of the best ways to find biomarkers for cancer detection, diagnosis and to provide novel insights into internal physiological state where subtle changes may happen in metabolite concentrations. Nuclear Magnetic Resonance (NMR) technique nowadays is a popular tool to analyze cell extracts, tissues and biological fluids, etc, since it is a relatively fast and an accurate technique to supply abundant biochemical information at molecular levels for tumor research. In this review, approaches in tumor metabolism are discussed, including sample collection, data profiling and multivariate data analysis methods etc. Some typical applications of NMR are also summarized in tumor metabolism.

Plasma metabolomic analysis of human hepatocellular carcinoma: Diagnostic and therapeutic study

Many hepatocellular carcinoma (HCC) patients suffer from late stages when diagnosed, leading to dismal prospects for cure. Improving the diagnosis and treatment of HCC remains a challenge. In this work, NMR-based metabolomic techniques were used to investigate the metabolic alterations of HCC patients from different pathological backgrounds. Metabolic improvement of clinical surgical treatments or transcatheter arterial chemoembolization (TACE) for recurrent or metastatic HCC was also evaluated. HCC was characterized by enhanced lipid metabolism and high consumption in response to liver injury. Expectedly, higher consumption of glucose and lactate production in TACE group confirmed that recurrent or metastatic HCC is more active in citric acid cycle and oxidative phosphorylation. However, TACE or surgical treatments did not immediately improve the metabolic profiles of HCC patients. Combining multivariate statistical analyses with univariate t-test, a series of characteristic metabolites were identified and served as biomarkers for discrimination of HCC patients in different pathological backgrounds. The relative metabolic pathway analyses help to get insight into the underlying biochemical mechanism and extend clinical relevance. Furthermore, algorithm of support vector classification was used to identify HCC and control subjects, and diagnostic sensitivity and specificity reached to 100% and 81.08% respectively by receiver operating characteristic analysis. It is concluded that NMR-based metabolomic analysis of plasma can provide a powerful approach to discover diagnostic and therapeutic biomarkers, and subsequently contribute to clinical disease management.

Discovery of urine biomarkers for bladder cancer via global metabolomics

Bladder cancer (BC) is latent in its early stage and lethal in its late stage. Therefore, early diagnosis and intervention are essential for successful BC treatment. Considering the limitations of current diagnostic tools, noninvasive biomarkers that are both highly sensitive and specific are needed to improve the overall survival and quality of life of patients. With the advent of systems biology, "-omics" technologies have been developed over the past few decades. As a promising member, global metabolomics has increasingly been found to have clear potential for biomarker discovery. However, urinary metabolomics studies related to BC have lagged behind those of other urinary cancers, and major findings have not been systematically reported. The objective of this review is to comprehensively list the currently identified potential urinary metabolite biomarkers for BC.

Metabolomics of Human Amniotic Fluid and Maternal Plasma during Normal Pregnancy

Metabolic profiles of amniotic fluid and maternal blood are sources of valuable information about fetus development and can be potentially useful in diagnosis of pregnancy disorders. In this study, we applied 1H NMR-based metabolic profiling to track metabolic changes occurring in amniotic fluid (AF) and plasma (PL) of healthy mothers over the course of pregnancy. AF and PL samples were collected in the 2nd (T2) and 3rd (T3) trimester, prolonged pregnancy (PP) until time of delivery (TD). A multivariate data analysis of both biofluids reviled a metabolic switch-like transition between 2nd and 3rd trimester, which was followed by metabolic stabilization throughout the rest of pregnancy probably reflecting the stabilization of fetal maturation and development. The differences were further tested using univariate statistics at α = 0.001. In plasma the progression from T2 to T3 was related to increasing levels of glycerol, choline and ketone bodies (3-hydroxybutyrate and acetoacetate) while pyruvate concentration was significantly decreased. In amniotic fluid, T2 to T3 transition was associated with decreasing levels of glucose, carnitine, amino acids (valine, leucine, isoleucine, alanine, methionine, tyrosine, and phenylalanine) and increasing levels of creatinine, succinate, pyruvate, choline, N,N-dimethylglycine and urocanate. Lactate to pyruvate ratio was decreased in AF and conversely increased in PL. The results of our study, show that metabolomics profiling can be used to better understand physiological changes of the complex interdependencies of the mother, the placenta and the fetus during pregnancy. In the future, these results might be a useful reference point for analysis of complicated pregnancies.

Metabolic phenotype of bladder cancer

Metabolism of bladder cancer represents a key issue for cancer research. Several metabolic altered pathways are involved in bladder tumorigenesis, representing therefore interesting targets for therapy. Tumor cells, including urothelial cancer cells, rely on a peculiar shift to aerobic glycolysis-dependent metabolism (the Warburg-effect) as the main energy source to sustain their uncontrolled growth and proliferation. Therefore, the high glycolytic flux depends on the overexpression of glycolysis-related genes (SRC-3, glucose transporter type 1 [GLUT1], GLUT3, lactic dehydrogenase A [LDHA], LDHB, hexokinase 1 [HK1], HK2, pyruvate kinase type M [PKM], and hypoxia-inducible factor 1-alpha [HIF-1α]), resulting in an overproduction of pyruvate, alanine and lactate. Concurrently, bladder cancer metabolism displays an increased expression of genes favoring the pentose phosphate pathway (glucose-6-phosphate dehydrogenase [G6PD]) and the fatty-acid synthesis (fatty acid synthase [FASN]), along with a decrease of AMP-activated protein kinase (AMPK) and Krebs cycle activities. Moreover, the PTEN/PI3K/AKT/mTOR pathway, hyper-activated in bladder cancer, acts as central regulator of aerobic glycolysis, hence contributing to cancer metabolic switch and tumor cell proliferation. Besides glycolysis, glycogen metabolism pathway plays a robust role in bladder cancer development. In particular, the overexpression of GLUT-1, the loss of the tumor suppressor glycogen debranching enzyme amylo-α-1,6-glucosidase, 4-α-glucanotransferase (AGL), and the increased activity of the tumor promoter enzyme glycogen phosphorylase impair glycogen metabolism. An increase in glucose uptake, decrease in normal cellular glycogen storage, and overproduction of lactate are consequences of decreased oxidative phosphorylation and inability to reuse glucose into the pentose phosphate and de novo fatty acid synthesis pathways. Moreover, AGL loss determines augmented levels of the serine-to-glycine enzyme serine hydroxymethyltransferase-2 (SHMT2), resulting in an increased glycine and purine ring of nucleotides synthesis, thus supporting cells proliferation. A deep understanding of the metabolic phenotype of bladder cancer will provide novel opportunities for targeted therapeutic strategies.

Biomarkers in bladder cancer: A metabolomic approach using in vitro and ex vivo model systems

Metabolomics has recently proved to be useful in the area of biomarker discovery for cancers in which early diagnostic and prognostic biomarkers are urgently needed, as is the case of bladder cancer (BC). This article presents a comprehensive review of the literature on the metabolomic studies on BC, highlighting metabolic pathways perturbed in this disease and the altered metabolites as potential biomarkers for BC detection. Current disease model systems used in the study of BC metabolome include in vitro-cultured cancer cells, ex vivo neoplastic bladder tissues and biological fluids, mainly urine but also blood serum/plasma, from BC patients. The major advantages and drawbacks of each model system are discussed. Based on available data, it seems that BC metabolic signature is mainly characterized by alterations in metabolites related to energy metabolic pathways, particularly glycolysis, amino acid and fatty acid metabolism, known to be crucial for cell proliferation, as well as glutathione metabolism, known to be determinant in maintaining cellular redox balance. In addition, purine and pyrimidine metabolism as well as carnitine species were found to be altered in BC. Finally, it is emphasized that, despite the progress made in respect to novel biomarkers for BC diagnosis, there are still some challenges and limitations that should be addressed in future metabolomic studies to ensure their translatability to clinical practice.

The strengths and weaknesses of NMR spectroscopy and mass spectrometry with particular focus on metabolomics research

Mass spectrometry (MS) and nuclear magnetic resonance (NMR) have evolved as the most common techniques in metabolomics studies, and each brings its own advantages and limitations. Unlike MS spectrometry, NMR spectroscopy is quantitative and does not require extra steps for sample preparation, such as separation or derivatization. Although the sensitivity of NMR spectroscopy has increased enormously and improvements continue to emerge steadily, this remains a weak point for NMR compared with MS. MS-based metabolomics provides an excellent approach that can offer a combined sensitivity and selectivity platform for metabolomics research. Moreover, different MS approaches such as different ionization techniques and mass analyzer technology can be used in order to increase the number of metabolites that can be detected. In this chapter, the advantages, limitations, strengths, and weaknesses of NMR and MS as tools applicable to metabolomics research are highlighted.

A cultured approach to canine urothelial carcinoma: molecular characterization of five cell lines

Background

Urothelial carcinoma (UC), also known as transitional cell carcinoma (TCC), of the bladder is the most common neoplasm affecting the canine urogenital system. To facilitate study of the disease in vitro, cell line models have been established from primary tumor biopsies. Their resemblance to the primary disease, however, has not been well defined. In the present study, we evaluated five canine UC cell lines via oligonucleotide array comparative genomic hybridization (oaCGH), fluorescence in situ hybridization (FISH), and gene expression analysis.

Results

Comparison of genome wide DNA copy number profiles of the cell lines with primary biopsy specimens revealed redundancies in genomic aberrations, indicating that the cell lines retain the gross genomic architecture of primary tumors. As in the primary tumors, gain of canine chromosomes 13 and 36 and loss of chromosome 19 were among the most frequent aberrations evident in the cell lines. FISH analysis revealed chromosome structural aberrations, including tandem duplications, bi-armed chromosomes, and chromosome fusions, suggesting genome instability during neoplastic transformation. Gene expression profiling highlighted numerous differentially expressed genes, including many previously shown as dysregulated in primary canine UC and human bladder cancer. Pathway enrichment analysis emphasized pathways suspected to be at the crux of UC pathogenesis, including xenobiotic and lipid compound metabolism.

Conclusions

These data support valid use of the canine UC cell lines evaluated by confirming they provide an accurate and practical means to interrogate the UC at a molecular level. Moreover, the cell lines may provide a valuable model for furthering our understanding of aberrant metabolic pathways in UC development.

Electronic supplementary material

The online version of this article (doi:10.1186/s40575-015-0028-3) contains supplementary material, which is available to authorized users.

Comparison of GC-MS and GC×GC-MS in the analysis of human serum samples for biomarker discovery

We compared the performance of gas chromatography time-of-flight mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) for metabolite biomarker discovery. Metabolite extracts from 109 human serum samples were analyzed on both platforms with a pooled serum sample analyzed after every 9 biological samples for the purpose of quality control (QC). The experimental data derived from the pooled QC samples showed that the GC×GC-MS platform detected about three times as many peaks as the GC-MS platform at a signal-to-noise ratio SNR ≥ 50, and three times the number of metabolites were identified by mass spectrum matching with a spectral similarity score Rsim ≥ 600. Twenty-three metabolites had statistically significant abundance changes between the patient samples and the control samples in the GC-MS data set while 34 metabolites in the GC×GC-MS data set showed statistically significant differences. Among these two groups of metabolite biomarkers, nine metabolites were detected in both the GC-MS and GC×GC-MS data sets with the same direction and similar magnitude of abundance changes between the control and patient sample groups. Manual verification indicated that the difference in the number of the biomarkers discovered using these two platforms was mainly due to the limited resolution of chromatographic peaks by the GC-MS platform, which can result in severe peak overlap making subsequent spectrum deconvolution for metabolite identification and quantification difficult.

Alteration of the fecal microbiota and serum metabolite profiles in dogs with idiopathic inflammatory bowel disease

Idiopathic inflammatory bowel disease (IBD) is a common cause of chronic gastrointestinal (GI) disease in dogs. The combination of an underlying host genetic susceptibility, an intestinal dysbiosis, and dietary/environmental factors are suspected as main contributing factors in the pathogenesis of canine IBD. However, actual mechanisms of the host-microbe interactions remain elusive. The aim of this study was to compare the fecal microbiota and serum metabolite profiles between healthy dogs (n = 10) and dogs with IBD before and after 3 weeks of medical therapy (n = 12). Fecal microbiota and metabolite profiles were characterized by 454-pyrosequencing of 16 S rRNA genes and by an untargeted metabolomics approach, respectively. Significantly lower bacterial diversity and distinct microbial communities were observed in dogs with IBD compared to the healthy control dogs. While Gammaproteobacteria were overrepresented, Erysipelotrichia, Clostridia, and Bacteroidia were underrepresented in dogs with IBD. The functional gene content was predicted from the 16 S rRNA gene data using PICRUSt, and revealed overrepresented bacterial secretion system and transcription factors, and underrepresented amino acid metabolism in dogs with IBD. The serum metabolites 3-hydroxybutyrate, hexuronic acid, ribose, and gluconic acid lactone were significantly more abundant in dogs with IBD. Although a clinical improvement was observed after medical therapy in all dogs with IBD, this was not accompanied by significant changes in the fecal microbiota or in serum metabolite profiles. These results suggest the presence of oxidative stress and a functional alteration of the GI microbiota in dogs with IBD, which persisted even in the face of a clinical response to medical therapy.

Standardizing the experimental conditions for using urine in NMR-based metabolomic studies with a particular focus on diagnostic studies: a review

The metabolic composition of human biofluids can provide important diagnostic and prognostic information. Among the biofluids most commonly analyzed in metabolomic studies, urine appears to be particularly useful. It is abundant, readily available, easily stored and can be collected by simple, noninvasive techniques. Moreover, given its chemical complexity, urine is particularly rich in potential disease biomarkers. This makes it an ideal biofluid for detecting or monitoring disease processes. Among the metabolomic tools available for urine analysis, NMR spectroscopy has proven to be particularly well-suited, because the technique is highly reproducible and requires minimal sample handling. As it permits the identification and quantification of a wide range of compounds, independent of their chemical properties, NMR spectroscopy has been frequently used to detect or discover disease fingerprints and biomarkers in urine. Although protocols for NMR data acquisition and processing have been standardized, no consensus on protocols for urine sample selection, collection, storage and preparation in NMR-based metabolomic studies have been developed. This lack of consensus may be leading to spurious biomarkers being reported and may account for a general lack of reproducibility between laboratories. Here, we review a large number of published studies on NMR-based urine metabolic profiling with the aim of identifying key variables that may affect the results of metabolomics studies. From this survey, we identify a number of issues that require either standardization or careful accounting in experimental design and provide some recommendations for urine collection, sample preparation and data acquisition.

The utility of metabolomics in natural product and biomarker characterization

BACKGROUND

Metabolomics is a well-established rapidly developing research field involving quantitative and qualitative metabolite assessment within biological systems. Recent improvements in metabolomics technologies reveal the unequivocal value of metabolomics tools in natural products discovery, gene-function analysis, systems biology and diagnostic platforms.

SCOPE OF REVIEW

We review here some of the prominent metabolomics methodologies employed in data acquisition and analysis of natural products and disease-related biomarkers.

MAJOR CONCLUSIONS

This review demonstrates that metabolomics represents a highly adaptable technology with diverse applications ranging from environmental toxicology to disease diagnosis. Metabolomic analysis is shown to provide a unique snapshot of the functional genetic status of an organism by examining its biochemical profile, with relevance toward resolving phylogenetic associations involving horizontal gene transfer and distinguishing subgroups of genera possessing high genetic homology, as well as an increasing role in both elucidating biosynthetic transformations of natural products and detecting preclinical biomarkers of numerous disease states.

GENERAL SIGNIFICANCE

This review expands the interest in multiplatform combinatorial metabolomic analysis. The applications reviewed range from phylogenetic assignment, biosynthetic transformations of natural products, and the detection of preclinical biomarkers.

Follicular adenomas exhibit a unique metabolic profile. ¹H NMR studies of thyroid lesions

Thyroid cancer is the most common endocrine malignancy. However, more than 90% of thyroid nodules are benign. It remains unclear whether thyroid carcinoma arises from preexisting benign nodules. Metabolomics can provide valuable and comprehensive information about low molecular weight compounds present in living systems and further our understanding of the biology regulating pathological processes. Herein, we applied ¹H NMR-based metabolic profiling to identify the metabolites present in aqueous tissue extracts of healthy thyroid tissue (H), non-neoplastic nodules (NN), follicular adenomas (FA) and malignant thyroid cancer (TC) as an alternative way of investigating cancer lesions. Multivariate statistical methods provided clear discrimination not only between healthy thyroid tissue and pathological thyroid tissue but also between different types of thyroid lesions. Potential biomarkers common to all thyroid lesions were identified, namely, alanine, methionine, acetone, glutamate, glycine, lactate, tyrosine, phenylalanine and hypoxanthine. Metabolic changes in thyroid cancer were mainly related to osmotic regulators (taurine and scyllo- and myo-inositol), citrate, and amino acids supplying the TCA cycle. Thyroid follicular adenomas were found to display metabolic features of benign non-neoplastic nodules and simultaneously displayed a partial metabolic profile associated with malignancy. This finding allows the discrimination of follicular adenomas from benign non-neoplastic nodules and thyroid cancer with similar accuracy. Moreover, the presented data indicate that follicular adenoma could be an individual stage of thyroid cancer development.

Low- and high-grade bladder cancer determination via human serum-based metabolomics approach

To address the shortcomings of urine cytology and cystoscopy for probing and grading urinary bladder cancer (BC), we applied (1)H nuclear magnetic resonance (NMR) spectroscopy as a surrogate method for the identification of BC. This study includes 99 serum samples comprising low-grade (LG; n = 36) and high-grade (HG; n = 31) BC as well as healthy controls (HC; n = 32). (1)H NMR-derived serum data were analyzed using orthogonal partial least-squares discriminant analysis (OPLS-DA). OPLS-DA-derived model validity was confirmed using an internal and external cross-validation. Internal validation was performed using the initial samples (n = 99) data set. External validation was performed on a new batch of suspected BC patients (n = 106) through a double-blind study. Receiver operating characteristic (ROC) curve analysis was also performed. OPLS-DA-derived serum metabolomics (six biomarkers, ROC; 0.99) were able to discriminate 95% of BC cases with 96% sensitivity and 94% specificity when compared to HC. Likewise (three biomarkers, ROC; 0.99), 98% of cases of LG were able to differentiate from HG with 97% sensitivity and 99% specificity. External validation reveals comparable results to the internal validation. (1)H NMR-based serum metabolic screening appears to be a promising and less invasive approach for probing and grading BC in contrast to the highly invasive and painful cystoscopic approach for BC detection.