Amygdalobacter indicium gen. nov., sp. nov., and Amygdalobacter nucleatus sp. nov., gen. nov.: novel bacteria from the family Oscillospiraceae isolated from the female genital tract.

Four obligately anaerobic Gram-positive bacteria representing one novel genus and two novel species were isolated from the female genital tract. Both novel species, designated UPII 610-JT and KA00274T, and an additional isolate of each species were characterized utilizing biochemical, genotypic and phylogenetic analyses. All strains were non-motile and non-spore forming, asaccharolytic, non-cellulolytic and indole-negative coccobacilli. Fatty acid methyl ester analysis for UPII 610-JT and KA00274T and additional isolates revealed C16 : 0, C18 : 0, C18:1ω9c and C18:2ω6,9c to be the major fatty acids for both species. UPII 610-JT had a 16S rRNA gene sequence similarity of 99.4 % to an uncultured clone sequence (AY724740) designated as Bacterial Vaginosis Associated Bacterium 2 (BVAB2). KA00274T had a 16S rRNA gene sequence similarity of 96.5 % to UPII 610-JT. Whole genomic DNA mol% G+C content was 42.2 and 39.3 % for UPII 610-JT and KA00274T, respectively. Phylogenetic analyses indicate these isolates represent a novel genus and two novel species within the Oscillospiraceae family. We propose the names Amygdalobacter indicium gen. nov., sp. nov., for UPII 610-JT representing the type strain of this species (=DSM 112989T, =ATCC TSD-274T) and Amygdalobacter nucleatus gen. nov., sp. nov., for KA00274T representing the type strain of this species (=DSM 112988T, =ATCC TSD-275T).

Use of sensitivity-enhanced nuclear magnetic resonance spectroscopy equipped with a 1.7-mm cryogenically cooled micro-coil probe in identifying human sperm intracellular metabolites.

CONTEXT: The clinical value of human sperm metabolites has not been established due to the technical complexity in detecting these metabolites when sperm numbers are low. AIMS: To detect endogenous intracellular metabolites in fresh and post-thaw human spermatozoa using 800MHz nuclear magnetic resonance (NMR) spectroscopy equipped with a 1.7-mm cryo-probe. METHODS: Processed spermatozoa from 25 normozoospermic ejaculates were subjected to extraction of intracellular metabolites and then profiled by sensitivity-enhanced NMR spectroscopy equipped with a 1.7-mm cryogenically cooled micro-coil probe. In parallel, some of the processed sperm fractions were subjected to freeze-thawing and were then analysed for intracellular metabolites. KEY RESULTS: Twenty-three metabolites were profiled from only 1.25million sperm cells. Comparison of the metabolomic signature of pre-freeze and post-thaw sperm cells did not show significant changes in the levels of metabolites. CONCLUSIONS: Sensitivity-enhanced NMR spectroscopy equipped with a 1.7-mm cryogenically cooled micro-coil probe is a potential tool for identifying intracellular metabolites when sperm number is low. IMPLICATIONS: Use of sensitivity-enhanced NMR spectroscopy opens up the opportunity to test for endogenous metabolites in samples with a limited number of spermatozoa, to understand the patho-physiology of infertility.

Biomarkers for Duchenne muscular dystrophy progression: impact of age in the mdx tongue spared muscle.

Background: Duchenne muscular dystrophy (DMD) is a severe form of muscular dystrophy without an effective treatment, caused by mutations in the DMD gene, leading to the absence of dystrophin. DMD results in muscle weakness, loss of ambulation and death at an early age. Metabolomics studies in mdx mice, the most used model for DMD, reveal changes in metabolites associated with muscle degeneration and aging. In DMD, the tongue muscles exhibit unique behavior, initially showing partial protection against inflammation but later experiencing fibrosis and loss of muscle fibers. Certain metabolites and proteins, like TNF-α and TGF-ß, are potential biomarkers for dystrophic muscle characterization. Methods: To investigate disease progression and aging, we utilized young (1-month old) and old (21-25 months old) mdx and wild-type mice. Metabolite changes were analyzed using 1-H Nuclear Magnetic Resonance, while TNF-α and TGF-ß were assessed using Western blotting to examine inflammation, and fibrosis. Morphometric analysis was conducted to assess the extent of myofiber damage between groups. Results: The histological analysis of the tongue showed no differences between groups. No differences were found between the concentrations of metabolites from wild type or mdx animals of the same age. The metabolites alanine, methionine, 3-methylhistidine were higher, and taurine and glycerol were lower in young animals in both wild type and mdx (p < 0.001). The metabolites glycine (p < 0.001) and glutamic acid (p = 0.0018) were different only in the mdx groups, being higher in young mdx mice. Acetic acid, phosphocreatine, isoleucine, succinic acid, creatine and the proteins TNF-α and TGF-ß had no difference in the analysis between groups (p > 0.05). Conclusions: Surprisingly, histological and protein analysis reveals that the tongue of young and old mdx animals is protected from severe myonecrosis observed in other muscles. The metabolites alanine, methionine, 3-methylhistidine, taurine, and glycerol may be effective for specific assessments, although their use for disease progression monitoring should be cautious due to age-related changes. Acetic acid, phosphocreatine, isoleucine, succinate, creatine, TNF-α, and TGF-ß do not vary with aging and remain constant in spared muscles, suggesting their potential as specific biomarkers for DMD progression independent of aging.

ICSI in non-male factor infertility patients does not alter metabolomic signature in sibling embryos as evidenced by sensitivity enhanced nuclear magnetic resonance (NMR) spectroscopy.

Intracytoplasmic sperm injection (ICSI) was developed to overcome male factor infertility, however, there recently has been an increasing trend in ICSI usage irrespective of the etiology, demonstrating an overuse of this insemination technique. There is a limited knowledge on the behaviour of ICSI derived embryos in non-male factor infertility patients. Metabolomic assessment of preimplantation embryos in conjunction with morphological evaluation can provide better understanding of embryonic behaviour. Hence, this study was undertaken to explore if there are any metabolomic differences between IVF and ICSI derived sibling day-5 blastocysts from non-male factor infertility patients. This prospective study included nineteen couples with non-male factor infertility undergoing Assisted Reproductive Technology. The sibling oocytes retrieved from each patient were randomly assigned to two groups and inseminated either by IVF or ICSI. Spent culture media (SCM) in which embryos were cultured up to day 5 were collected and investigated using sensitivity enhanced NMR based metabolite profiling utilizing high resolution (800 MHz) NMR equipped with cryogenically cooled micro-coil (1.7 mm) probe. The metabolomic signature between IVF and ICSI derived sibling blastocysts was assessed. A significant reduction in the concentrations of pyruvate, citrate, glucose and lysine were observed in both IVF and ICSI sibling embryos compared to medium control (P< 0.05-0.001). Further, histidine and valine level was found lower in ICSI embryos compared to medium control (P<0.05) during 96 hours of in vitro culture. Notably, between IVF and ICSI SCM, no significant difference in the concentration of the metabolites was found. Our results suggest that ICSI in non-male factor does not alter the SCM metabolomic signature during 96 hours of embryonic development.

Duration of dry and humidified incubation of single-step embryo culture medium and oxygen tension during sham culture do not alter medium composition.

Background: The extended embryo culture using single-step medium gained popularity in clinical in vitro fertilisation (IVF). However, there are concerns about the degradation of unstable medium components and their negative effects on the developing embryos. Further, dry-incubation can increase osmolality, which can in-turn enhance the concentration of constituents of the media and their stability. Hence, this study was conducted to understand the immediate changes in the culture media metabolites in relation to clinically comparable situations such as single-step extended embryo culture and use of dry and humidified-incubation in two-different gaseous conditions. Methods: Commercially available single-step medium was sham-cultured in droplets under oil in two different conditions viz. dry (37°C; 6%CO 2; 5%O 2) and humidified (37°C; 6% CO 2; atmospheric O 2) for 0h, 72h, and 120h intervals. Droplets were subjected to the sensitivity-enhanced nuclear magnetic resonance (NMR)-based profiling using 800 MHz NMR equipped with a cryogenically cooled micro-coil (1.7mm) probe. Metabolomic signatures between the two groups were comprehensively assessed. Results: A total of ten amino acids and four energy substrates were identified from the culture medium. Metabolite levels showed a non-significant increase in the dry-incubation group at 72h and then declined at 120h. Humidified incubation had no effects on the level of the metabolite until 120h. No significant differences in the levels of metabolites were observed between the dry and humidified-groups at various time-points tested. Conclusions: A non-significant variation in the levels of metabolites observed in the dry-incubation of single-step medium most unlikely to influence a clinical outcome. However, the impact of these subtle changes on the (epi)genetic integrity of the embryos in a clinical set-up to be addressed.

Biomarker-Calibrated Red and Combined Red and Processed Meat Intakes with Chronic Disease Risk in a Cohort of Postmenopausal Women.

BACKGROUND: The associations of red and processed meat with chronic disease risk remain to be clarified, in part because of measurement error in self-reported diet. OBJECTIVES: We sought to develop metabolomics-based biomarkers for red and processed meat, and to evaluate associations of biomarker-calibrated meat intake with chronic disease risk among postmenopausal women. METHODS: Study participants were women who were members of the Women's Health Initiative (WHI) study cohorts. These participants were postmenopausal women aged 50-79 y when enrolled during 1993-1998 at 40 US clinical centers with embedded human feeding and nutrition biomarker studies. Literature reports of metabolomics correlates of meat consumption were used to develop meat intake biomarkers from serum and 24-h urine metabolites in a 153-participant feeding study (2010-2014). Resulting biomarkers were used in a 450-participant biomarker study (2007-2009) to develop linear regression calibration equations that adjust FFQ intakes for random and systematic measurement error. Biomarker-calibrated meat intakes were associated with cardiovascular disease, cancer, and diabetes incidence among 81,954 WHI participants (1993-2020). RESULTS: Biomarkers and calibration equations meeting prespecified criteria were developed for consumption of red meat and red plus processed meat combined, but not for processed meat consumption. Following control for nondietary confounding factors, hazard ratios were calculated for a 40% increment above the red meat median intake for coronary artery disease (HR: 1.10; 95% CI: 1.07, 1.14), heart failure (HR: 1.26; 95% CI: 1.20, 1.33), breast cancer (HR: 1.10; 95% CI: 1.07, 1.13) for, total invasive cancer (HR: 1.07; 95% CI: 1.05, 1.09), and diabetes (HR: 1.37; 95% CI: 1.34, 1.39). HRs for red plus processed meat intake were similar. HRs were close to the null, and mostly nonsignificant following additional control for dietary potential confounding factors, including calibrated total energy consumption. CONCLUSIONS: A relatively high-meat dietary pattern is associated with somewhat higher chronic disease risks. These elevations appear to be largely attributable to the dietary pattern, rather than to consumption of red or processed meat per se.

Four-Day Food Record Macronutrient Intake, With and Without Biomarker Calibration, and Chronic Disease Risk in Postmenopausal Women.

We recently evaluated associations of biomarker-calibrated protein intake, protein density, carbohydrate intake, and carbohydrate density with the incidence of cardiovascular disease, cancer, and diabetes among postmenopausal women in the Women's Health Initiative (1993-present, 40 US clinical centers). The biomarkers relied on serum and urine metabolomics profiles, and biomarker calibration used regression of biomarkers on food frequency questionnaires. Here we develop corresponding calibration equations using food records and dietary recalls. In addition, we use calibrated intakes based on food records in disease association estimation in a cohort subset (n = 29,294) having food records. In this analysis, more biomarker variation was explained by food records than by FFQs for absolute macronutrient intake, with 24-hour recalls being intermediate. However, the percentage of biomarker variation explained was similar for each assessment approach for macronutrient densities. Invasive breast cancer risk was related inversely to carbohydrate and protein densities using food records, in analyses that included (calibrated) total energy intake and body mass index. Corresponding analyses for absolute intakes did not differ from the null, nor did absolute or relative intakes associate significantly with colorectal cancer or coronary heart disease. These analyses do not suggest major advantages for food records or dietary recalls in comparison with less costly and logistically simpler food frequency questionnaires for these nutritional variables.

Biomarkers for Components of Dietary Protein and Carbohydrate with Application to Chronic Disease Risk in Postmenopausal Women.

BACKGROUND: We recently developed protein and carbohydrate intake biomarkers using metabolomics profiles in serum and urine, and used them to correct self-reported dietary data for measurement error. Biomarker-calibrated carbohydrate density was inversely associated with chronic disease risk, whereas protein density associations were mixed. OBJECTIVES: To elucidate and extend this earlier work through biomarker development for protein and carbohydrate components, including animal protein and fiber. METHODS: Prospective disease association analyses were undertaken in Women's Health Initiative (WHI) cohorts of postmenopausal US women, aged 50-79 y when enrolled at 40 US clinical centers. Biomarkers were developed using an embedded human feeding study (n = 153). Calibration equations for protein and carbohydrate components were developed using a WHI nutritional biomarker study (n = 436). Calibrated intakes were associated with chronic disease incidence in WHI cohorts (n = 81,954) over a 20-y (median) follow-up period, using HR regression methods. RESULTS: Previously reported elevations in cardiovascular disease (CVD) with higher-protein diets tended to be explained by animal protein density. For example, for coronary heart disease a 20% increment in animal protein density had an HR of 1.20 (95% CI: 1.02, 1.42) relative to the HR for total protein density. In comparison, cancer and diabetes risk showed little association with animal protein density beyond that attributable to total protein density. Inverse carbohydrate density associations with total CVD were mostly attributable to fiber density, with a 20% increment HR factor of 0.89 (95% CI: 0.83, 0.94). Cancer risk showed little association with fiber density, whereas diabetes risk had a 20% increment HR of 0.93 (95% CI: 0.88, 0.98) relative to the HRs for total carbohydrate density. CONCLUSIONS: In a population of postmenopausal US women, CVD risk was associated with high-animal-protein and low-fiber diets, cancer risk was associated with low-carbohydrate diets, and diabetes risk was associated with low-fiber/low-carbohydrate diets.

Evaluation of potential metabolomic-based biomarkers of protein, carbohydrate and fat intakes using a controlled feeding study.

PURPOSE: Objective biomarkers of dietary exposure are needed to establish reliable diet-disease associations. Unfortunately, robust biomarkers of macronutrient intakes are scarce. We aimed to assess the utility of serum, 24-h urine and spot urine high-dimensional metabolites for the development of biomarkers of daily intake of total energy, protein, carbohydrate and fat, and the percent of energy from these macronutrients (%E). METHODS: A 2-week controlled feeding study mimicking the participants' habitual diets was conducted among 153 postmenopausal women from the Women's Health Initiative (WHI). Fasting serum metabolomic profiles were analyzed using a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for aqueous metabolites and a direct-injection-based quantitative lipidomics platform. Urinary metabolites were analyzed using 1H nuclear magnetic resonance (NMR) spectroscopy at 800 MHz and by untargeted gas chromatography-mass spectrometry (GC-MS). Variable selection was performed to build prediction models for each dietary variable. RESULTS: The highest cross-validated multiple correlation coefficients (CV-R2) for protein intake (%E) and carbohydrate intake (%E) using metabolites only were 36.3 and 37.1%, respectively. With the addition of established dietary biomarkers (doubly labeled water for energy and urinary nitrogen for protein), the CV-R2 reached 55.5% for energy (kcal/d), 52.0 and 45.0% for protein (g/d, %E), 55.9 and 37.0% for carbohydrate (g/d, %E). CONCLUSION: Selected panels of serum and urine metabolites, without the inclusion of doubly labeled water and urinary nitrogen biomarkers, give a reliable and robust prediction of daily intake of energy from protein and carbohydrate.

Biomarker-Calibrated Macronutrient Intake and Chronic Disease Risk among Postmenopausal Women.

BACKGROUND: Knowledge about macronutrient intake and chronic disease risk has been limited by the absence of objective macronutrient measures. Recently, we proposed novel biomarkers for protein, protein density, carbohydrate, and carbohydrate density, using established biomarkers and serum and urine metabolomics profiles in a human feeding study. OBJECTIVES: We aimed to use these biomarkers to develop calibration equations for macronutrient variables using dietary self-reports and personal characteristics and to study the association between biomarker-calibrated intake estimates and cardiovascular disease, cancer, and diabetes risk in Women's Health Initiative (WHI) cohorts. METHODS: Prospective disease association analyses are based on WHI cohorts of postmenopausal US women aged 50-79 y when enrolled at 40 US clinical centers (n = 81,954). We used biomarker intake values in a WHI nutritional biomarker study (n = 436) to develop calibration equations for each macronutrient variable, leading to calibrated macronutrient intake estimates throughout WHI cohorts. We then examined the association of these intakes with chronic disease incidence over a 20-y (median) follow-up period using HR regression methods. RESULTS: In analyses that included doubly labeled water-calibrated total energy, HRs for cardiovascular diseases and cancers were mostly unrelated to calibrated protein density. However, many were inversely related to carbohydrate density, with HRs (95% CIs) for a 20% increment in carbohydrate density of 0.81 (0.69, 0.95) and 0.83 (0.74, 0.93), respectively, for primary outcomes of coronary heart disease and breast cancer, as well as 0.74 (0.60, 0.91) and 0.87 (0.81, 0.93) for secondary outcomes of heart failure and total invasive cancer. Corresponding HRs (95% CIs) for type 2 diabetes incidence in relation to protein density and carbohydrate density were 1.17 (1.09, 1.75) and 0.73 (0.66, 0.80), respectively. CONCLUSIONS: At specific energy intake, a diet high in carbohydrate density is associated with substantially reduced risk of major chronic diseases in a population of US postmenopausal women. This trial was registered at clinicaltrials.gov as NCT00000611.

NMR Spectroscopy for Metabolomics Research.

Over the past two decades, nuclear magnetic resonance (NMR) has emerged as one of the three principal analytical techniques used in metabolomics (the other two being gas chromatography coupled to mass spectrometry (GC-MS) and liquid chromatography coupled with single-stage mass spectrometry (LC-MS)). The relative ease of sample preparation, the ability to quantify metabolite levels, the high level of experimental reproducibility, and the inherently nondestructive nature of NMR spectroscopy have made it the preferred platform for long-term or large-scale clinical metabolomic studies. These advantages, however, are often outweighed by the fact that most other analytical techniques, including both LC-MS and GC-MS, are inherently more sensitive than NMR, with lower limits of detection typically being 10 to 100 times better. This review is intended to introduce readers to the field of NMR-based metabolomics and to highlight both the advantages and disadvantages of NMR spectroscopy for metabolomic studies. It will also explore some of the unique strengths of NMR-based metabolomics, particularly with regard to isotope selection/detection, mixture deconvolution via 2D spectroscopy, automation, and the ability to noninvasively analyze native tissue specimens. Finally, this review will highlight a number of emerging NMR techniques and technologies that are being used to strengthen its utility and overcome its inherent limitations in metabolomic applications.

Megasphaera lornae sp. nov., Megasphaera hutchinsoni sp. nov., and Megasphaera vaginalis sp. nov.: novel bacteria isolated from the female genital tract.

Six strictly anaerobic Gram-negative bacteria representing three novel species were isolated from the female reproductive tract. The proposed type strains for each species were designated UPII 199-6T, KA00182T and BV3C16-1T. Phylogenetic analyses based on 16S rRNA gene sequencing indicated that the bacterial isolates were members of the genus Megasphaera. UPII 199-6T and KA00182T had 16S rRNA gene sequence identities of 99.9 % with 16S rRNA clone sequences previously amplified from the human vagina designated as Megasphaera type 1 and Megasphaera type 2, members of the human vaginal microbiota associated with bacterial vaginosis, preterm birth and HIV acquisition. UPII 199-6T exhibited sequence identities ranging from 92.9 to 93.6 % with validly named Megasphaera isolates and KA00182T had 16S rRNA gene sequence identities ranging from 92.6-94.2 %. BV3C16-1T was most closely related to Megasphaera cerevisiae with a 16S rRNA gene sequence identity of 95.4 %. Cells were coccoid or diplococcoid, non-motile and did not form spores. Genital tract isolates metabolized organic acids but were asaccharolytic. The isolates also metabolized amino acids. The DNA G+C content for the genome sequences of UPII 199-6T, KA00182T and BV3C16-1T were 46.4, 38.9 and 49.8 mol%, respectively. Digital DNA-DNA hybridization and average nucleotide identity between the genital tract isolates and other validly named Megasphaera species suggest that each isolate type represents a new species. The major fatty acid methyl esters include the following: C12 : 0, C16 : 0, C16 : 0 dimethyl acetal (DMA) and summed feature 5 (C15 : 0 DMA and/or C14 : 0 3-OH) in UPII 199-6T; C16 : 0 and C16 : 1 cis 9 in KA00182T; C12 : 0; C14 : 0 3-OH; and summed feature 5 in BV3C16-1T. The isolates produced butyrate, isobutyrate, and isovalerate but there were specific differences including production of formate and propionate. Together, these data indicate that UPII 199-6T, KA00182T and BV3C16-1T represent novel species within the genus Megasphaera. We propose the following names: Megasphaera lornae sp. nov. for UPII 199-6T representing the type strain of this species (=DSM 111201T=ATCC TSD-205T), Megasphaera hutchinsoni sp. nov. for KA00182T representing the type strain of this species (=DSM 111202T=ATCC TSD-206T) and Megasphaera vaginalis sp. nov. for BV3C16-1T representing the type strain of this species (=DSM 111203T=ATCC TSD-207T).

Profiling Redox and Energy Coenzymes in Whole Blood, Tissue and Cells Using NMR Spectroscopy.

Coenzymes of cellular redox reactions and cellular energy, as well as antioxidants mediate biochemical reactions fundamental to the functioning of all living cells. Conventional analysis methods lack the opportunity to evaluate these important redox and energy coenzymes and antioxidants in a single step. Major coenzymes include redox coenzymes: NAD⁺ (oxidized nicotinamide adenine dinucleotide), NADH (reduced nicotinamide adenine dinucleotide), NADP⁺ (oxidized nicotinamide adenine dinucleotide phosphate) and NADPH (reduced nicotinamide adenine dinucleotide phosphate); energy coenzymes: ATP (adenosine triphosphate), ADP (adenosine diphosphate) and AMP (adenosine monophosphate); and antioxidants: GSSG (oxidized glutathione) and GSH (reduced glutathione). We show here that a simple ¹H NMR experiment can measure these coenzymes and antioxidants in tissue and whole blood apart from a vast pool of other metabolites. In addition, focused on the goal of identification of coenzymes in subcellular fractions, we demonstrate analysis of coenzymes in the cytoplasm using breast cancer cells. Owing to their unstable nature, or low concentrations, most of the coenzymes either evade detection or lose their integrity when established sample preparation and analysis methods are used. To overcome this challenge, here we describe the development of new methods to detect these molecules without affecting the integrity of other metabolites. We used an array of 1D and 2D NMR methods, chemical shift databases, pH measurements and spiking with authentic compounds to establish the identity of peaks for the coenzymes and antioxidants in NMR spectra. Interestingly, while none of the coenzymes and antioxidants were detected in plasma, they were abundant in whole blood. Considering that the coenzymes and antioxidants represent a sensitive measure of human health and risk for numerous diseases, the presented NMR methods to measure them in one step potentially open new opportunities in the metabolomics field.

Metabolic profiles of triple-negative and luminal A breast cancer subtypes in African-American identify key metabolic differences.

Breast cancer, a heterogeneous disease with variable pathophysiology and biology, is classified into four major subtypes. While hormonal- and antibody-targeted therapies are effective in the patients with luminal and HER-2 subtypes, the patients with triple-negative breast cancer (TNBC) subtype do not benefit from these therapies. The incidence rates of TNBC subtype are higher in African-American women, and the evidence indicates that these women have worse prognosis compared to women of European descent. The reasons for this disparity remain unclear but are often attributed to TNBC biology. In this study, we performed metabolic analysis of breast tissues to identify how TNBC differs from luminal A breast cancer (LABC) subtypes within the African-American and Caucasian breast cancer patients, respectively. We used High-Resolution Magic Angle Spinning (HR-MAS) 1H Nuclear magnetic resonance (NMR) to perform the metabolomic analysis of breast cancer and adjacent normal tissues (total n=82 samples). TNBC and LABC subtypes in African American women exhibited different metabolic profiles. Metabolic profiles of these subtypes were also distinct from those revealed in Caucasian women. TNBC in African-American women expressed higher levels of glutathione, choline, and glutamine as well as profound metabolic alterations characterized by decreased mitochondrial respiration and increased glycolysis concomitant with decreased levels of ATP. TNBC in Caucasian women was associated with increased pyrimidine synthesis. These metabolic alterations could potentially be exploited as novel treatment targets for TNBC.

Metabolically distinct weight loss by 10,12 CLA and caloric restriction highlight the importance of subcutaneous white adipose tissue for glucose homeostasis in mice.

BACKGROUND: Widely used as a weight loss supplement, trans-10,cis-12 conjugated linoleic acid (10,12 CLA) promotes fat loss in obese mice and humans, but has also been associated with insulin resistance. OBJECTIVE: We therefore sought to directly compare weight loss by 10,12 CLA versus caloric restriction (CR, 15-25%), an acceptable healthy method of weight loss, to determine how 10,12 CLA-mediated weight loss fails to improve glucose metabolism. METHODS: Obese mice with characteristics of human metabolic syndrome were either supplemented with 10,12 CLA or subjected to CR to promote weight loss. Metabolic endpoints such as energy expenditure, glucose and insulin tolerance testing, and trunk fat distribution were measured. RESULTS: By design, 10,12 CLA and CR caused equivalent weight loss, with greater fat loss by 10,12 CLA accompanied by increased energy expenditure, reduced respiratory quotient, increased fat oxidation, accumulation of alternatively activated macrophages, and browning of subcutaneous white adipose tissue (WAT). Moreover, 10,12 CLA-supplemented mice better defended their body temperature against a cold challenge. However, 10,12 CLA concurrently induced the detrimental loss of subcutaneous WAT without reducing visceral WAT, promoted reduced plasma and WAT adipokine levels, worsened hepatic steatosis, and failed to improve glucose metabolism. Obese mice undergoing CR were protected from subcutaneous-specific fat loss, had improved hepatic steatosis, and subsequently showed the expected improvements in WAT adipokines, glucose metabolism and WAT inflammation. CONCLUSIONS: These results suggest that 10,12 CLA mediates the preferential loss of subcutaneous fat that likely contributes to hepatic steatosis and maintained insulin resistance, despite significant weight loss and WAT browning in mice. Collectively, we have shown that weight loss due to 10,12 CLA supplementation or CR results in dramatically different metabolic phenotypes, with the latter promoting a healthier form of weight loss.

Altered metabolite levels and correlations in patients with colorectal cancer and polyps detected using seemingly unrelated regression analysis.

Introduction: Metabolomics technologies enable the identification of putative biomarkers for numerous diseases; however, the influence of confounding factors on metabolite levels poses a major challenge in moving forward with such metabolites for pre-clinical or clinical applications. Objectives: To address this challenge, we analyzed metabolomics data from a colorectal cancer (CRC) study, and used seemingly unrelated regression (SUR) to account for the effects of confounding factors including gender, BMI, age, alcohol use, and smoking. Methods: A SUR model based on 113 serum metabolites quantified using targeted mass spectrometry, identified 20 metabolites that differentiated CRC patients (n = 36), patients with polyp (n = 39), and healthy subjects (n = 83). Models built using different groups of biologically related metabolites achieved improved differentiation and were significant for 26 out of 29 groups. Furthermore, the networks of correlated metabolites constructed for all groups of metabolites using the ParCorA algorithm, before or after application of the SUR model, showed significant alterations for CRC and polyp patients relative to healthy controls. Results: The results showed that demographic covariates, such as gender, BMI, BMI2, and smoking status, exhibit significant confounding effects on metabolite levels, which can be modeled effectively. Conclusion: These results not only provide new insights into addressing the major issue of confounding effects in metabolomics analysis, but also shed light on issues related to establishing reliable biomarkers and the biological connections between them in a complex disease.

Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis.

NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to nondestructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Precise metabolite quantification is a prerequisite to move any chemical biomarker or biomarker panel from the lab to the clinic. Among the biofluids commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, and easily obtained, needs little sample preparation, and does not require invasive medical procedures for collection. Furthermore, urine captures and concentrates many "unwanted" or "undesirable" compounds throughout the body, providing a rich source of potentially useful disease biomarkers; however, incredible variation in urine chemical concentrations makes analysis of urine and identification of useful urinary biomarkers by NMR challenging. We discuss a number of the most significant issues regarding NMR-based urinary metabolomics with specific emphasis on metabolite quantification for disease biomarker applications and propose data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, sample preparation, and biomarker assessment.