Publications
68 results found
Cai M, Edwards C, Tashkova M, et al., 2023, Cell wall matrices in chickpeas and their effects on starch digestion and postprandial metabolism, Winter Conference 2022/23,Architecture of food: processing, structure and health, Publisher: Cambridge University Press, ISSN: 0029-6651
Karampatsas K, Faal A, Jaiteh M, et al., 2022, Gastrointestinal, vaginal, nasopharyngeal, and breast milk microbiota profiles and breast milk metabolomic changes in Gambian infants over the first two months of lactation: a prospective cohort study, Medicine, Vol: 101, Pages: 1-10, ISSN: 0025-7974
Background: Microbiota composition in breast milk affects intestinal and respiratory microbiota colonization and the mucosal immune system's development in infants. The metabolomic content of breast milk is thought to interact with the microbiota and may influence developing infant immunity.Methods: 107 Gambian mothers and their healthy, vaginally delivered, exclusively breastfed infants were included in our study. We analyzed 32 breast milk samples, 51 maternal rectovaginal swabs and 30 infants' rectal swabs at birth. We also analyzed 9 breast milk samples and 18 infants' nasopharyngeal swabs 60 days post-delivery. We used 16S rRNA genesequencing to determine the microbiota composition. Metabolomic profiling analysis was performed on colostrum and mature breast milk samples using a multiplatform approach combining 1-H Nuclear Magnetic Resonance Spectroscopy and Gas Chromatography-Mass Spectrometry.Results: Bacterial communities were distinct in composition and diversity across different sample types. Breast milk composition changed over the first 60 days of lactation. α-1,4- and α-1,3-fucosylated human milk oligosaccharides, and other 33 key metabolites in breast milk(monosaccharides, sugar alcohols and fatty acids) increased between birth and day of 60 life.Conclusions: This study's results indicate that infant gut and respiratory microbiota are unique bacterial communities, distinct from maternal gut and breast milk, respectively. Breast milk microbiota composition and metabolomic profile change throughout lactation. These changesmay contribute to the infant's immunological, metabolic, and neurological development and could consist the basis for future interventions to correct disrupted early life microbial colonization.
Brignardello J, Fountana S, Posma JM, et al., 2022, Characterization of diet-dependent temporal changes in circulating short-chain fatty acid concentrations: a randomized crossover dietary trial, The American Journal of Clinical Nutrition, Vol: 116, Pages: 1368-1378, ISSN: 0002-9165
Background: Production of Short-chain fatty acids (SCFAs) from food is a complex and dynamic saccharolytic fermentation process mediated by both human and gut microbial factors. SCFA production and knowledge of the relationship between SCFA profiles and dietary patterns is lacking. Objective: Temporal changes in SCFA levels in response to two contrasting diets were investigated using a novel GC-MS method.Design: Samples were obtained from a randomized, controlled, crossover trial designed to characterize the metabolic response to four diets. Participants (n=19) undertook these diets during an inpatient stay (of 72-h). Serum samples were collected 2-h after breakfast (AB), lunch (AL) and dinner (AD) on day 3 and a fasting sample (FA) was obtained on day 4. 24-h urine samples were collected on day 3. In this sub-study, samples from the two extreme diets representing a diet with high adherence to WHO healthy eating recommendations and a typical Western diet were analyzed using a bespoke GC-MS method developed to detect and quantify 10 SCFAs and precursors in serum and urine samples. Results: Considerable inter-individual variation in serum SCFA concentrations was observed across all time points and temporal fluctuations were observed for both diets. Although the sample collection timing exerted a greater magnitude of effect on circulating SCFA concentrations, the unhealthy diet was associated with a lower concentration of acetic acid (FA: coefficient=-17.0; standard error (SE)=5.8; p-trend=0.00615), 2-methylbutyric acid (AL: coefficient=-0.1; SE=0.028; p-trend=4.13x10-4 and AD: coefficient =-0.1; SE:=0.028; p-trend=2.28x10-3) and 2-hydroxybutyric acid (FA: coefficient=-15.8; standard error=5.11; p-trend: 4.09x10-3). In contrast lactic acid was significantly higher in the unhealthy diet (AL: coefficient=750.2; standard error=315.2; p-trend=0.024 and AD: coefficient=1219.3; standard error=322.6; p-trend: 8.28x10-4). Conclusion: The GC-MS method allowed robust mapping of
Penney N, Yeung K, Garcia Perez I, et al., 2022, Multi-omic phenotyping reveals host-microbe responses to bariatric surgery, glycaemic control and obesity, communications medicine, Vol: 2, Pages: 1-18, ISSN: 2730-664X
Background: Resolution of type 2 diabetes (T2D) is common following bariatric surgery, particularly Roux-en-Y gastric bypass. However, the underlying mechanisms have not been fully elucidated.Methods: To address this we compare the integrated serum, urine and faecal metabolic profiles of participants with obesity +/- T2D (n=80, T2D=42) with participants who underwent Roux-en-Y gastric bypass or sleeve gastrectomy (pre and 3-months post-surgery; n=27), taking diet into account. We co-model these data with shotgun metagenomic profiles of the gut microbiota to provide a comprehensive atlas of host-gut microbe responses to bariatric surgery, weight-loss and glycaemic control at the systems level.Results: Here we show that bariatric surgery reverses several disrupted pathways characteristic of T2D. The differential metabolite set representative of bariatric surgery overlaps with both diabetes (19.3% commonality) and body mass index (18.6% commonality). However, the percentage overlap between diabetes and body mass index is minimal (4.0% commonality), consistent with weight-independent mechanisms of T2D resolution. The gut microbiota is more strongly correlated to body mass index than T2D, although we identify some pathways such as amino acid metabolism that correlate with changes to the gut microbiota and which influence glycaemic control.Conclusion: We identify multi-omic signatures associated with responses to surgery, body mass index, and glycaemic control. Improved understanding of gut microbiota - host co-metabolism may lead to novel therapies for weight-loss or diabetes. However, further experiments are required to provide mechanistic insight into the role of the gut microbiota in host metabolism and establish proof of causality.
Mujagic Z, Kasapi M, Jonkers DMAE, et al., 2022, Integrated fecal microbiome–metabolome signatures reflect stress and serotonin metabolism in irritable bowel syndrome, Gut Microbes, Vol: 14, Pages: 1-20, ISSN: 1949-0976
To gain insight into the complex microbiome-gut-brain axis in irritable bowel syndrome (IBS) several modalities of biological and clinical data must be combined. We aimed to identify profiles of faecal microbiota and metabolites associated with IBS and to delineate specific phenotypes of IBS that represent potential pathophysiological mechanisms. Faecal metabolites were measured using proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy and gut microbiome using Shotgun Metagenomic Sequencing (MGS) in a combined dataset of 142 IBS patients and 120 healthy controls (HC) with extensive clinical, biological and phenotype information. Data were analysed using support vector classification and regression and kernel t-SNE. Microbiome and metabolome profiles could distinguish IBS and HC with an area-under-the-receiver-operator-curve (AUC) of 77.3% and 79.5%, respectively, but this could be improved by combining microbiota and metabolites to 83.6%. No significant differences in predictive ability of the microbiome-metabolome data were observed between the three classical, stool pattern-based, IBS subtypes. However, unsupervised clustering showed distinct subsets of IBS patients based on faecal microbiome-metabolome data. These clusters could be related plasma levels of serotonin and its metabolite 5-hydroxyindoleacetate, effects of psychological stress on gastrointestinal symptoms, onset of IBS after stressful events, medical history of previous abdominal surgery, dietary caloric intake and IBS symptom duration. Furthermore, pathways in metabolic reaction networks were integrated with microbiota data, that reflect the host-microbiome interactions in IBS. The identified microbiome-metabolome signatures for IBS, associated with altered serotonin metabolism and unfavourable stress-response related to gastrointestinal symptoms, support the microbiota-gut-brain link in the pathogenesis of IBS.
Abbott K, Posma JM, Garcia Perez I, et al., 2022, Evidence-Based Tools for Dietary Assessments in Nutrition Epidemiology Studies for Dementia Prevention, The journal of prevention of Alzheimer's disease, ISSN: 2274-5807
Increasing evidence proposes diet as a notable modifiable factor and viable target for the reduction of Alzheimer’s Disease risk and age-related cognitive decline. However, assessment of dietary exposures is challenged by dietary capture methods that are prone to misreporting and measurement errors. The utility of -omics technologies for the evaluation of dietary exposures has the potential to improve reliability and offer new insights to pre-disease indicators and preventive targets in cognitive aging and dementia. In this review, we present a focused overview of metabolomics as a validation tool and framework for investigating the immediate or cumulative effects of diet on cognitive health.
Wu Y, Posma JM, Holmes E, et al., 2021, Odd chain fatty acids are not robust biomarkers for dietary intake of fiber, Molecular Nutrition and Food Research, Vol: 65, Pages: 1-8, ISSN: 1613-4125
Prior investigation has suggested a positive association between increased colonic propionate production and circulating odd-chain fatty acids [(OCFAs; pentadecanoic acid (C15:0), heptadecanoic acid (C17:0)]. As the major source of propionate in humans is the microbial fermentation of dietary fiber, OCFAs have been proposed as candidate biomarkers of dietary fiber. The objective of this study is to critically assess the plausibility, robustness, reliability, dose-response, time-response aspects of OCFAs as potential biomarkers of fermentable fibers in two independent studies using a validated analytical method. OCFAs were first assessed in a fiber supplementation study, where 21 participants received 10g dietary fiber supplementation for 7 days with blood samples collected on the final day at a 420 minute study visit. OCFAs were then assessed in a highly controlled inpatient setting, which 19 participants consumed a high fiber (45.1g/day) and a low fiber diet (13.6g/day) for 4 days. Collectively in both studies, dietary intakes of fiber as fiber supplementations or having consumed a high fiber diet did not increase circulating levels of OCFAs. The dose and temporal relations were not observed. Current study has generated new insight on the utility of OCFAs as fiber biomarkers and highlighted the importance of critical assessment of candidate dietary biomarkers before application.
Posma JM, Garcia-Perez I, Frost G, et al., 2021, Nutriome-metabolome relationships provide insights into dietary intake and metabolism (vol 1, pg 426, 2020), NATURE FOOD, Vol: 2, Pages: 541-542
Posma JM, Stamler J, Garcia-Perez I, et al., 2021, Urinary metabolic phenotype of blood pressure, 19TH INTERNATIONAL SHR SYMPOSIUM SHR, Publisher: Lippincott, Williams & Wilkins, Pages: E70-E70, ISSN: 0263-6352
Objective: Metabolic phenotyping (metabolomics) captures systems-level information on metabolic processes by simultaneously measuring hundreds of metabolites using spectroscopic techniques. Concentrations of these metabolites are affected by genetic (host, microbiome), environmental and dietary factors and may provide insights into biochemical pathways underlying raised blood pressure (BP) in populations.Design and method: Two separate, timed 24hr urine specimens were obtained from 2,031 women and men, aged 40–59, from 8 USA population samples in the INTERMAP Study. Proton Nuclear Magnetic Resonance (1H NMR) was used to characterize a urinary metabolic signature; this was unaffected by diurnal variability and sampling time as it captures end-products of metabolism over a 24hr period. Demographic, population, medical, lifestyle and anthropometric factors were accounted for in regression models to define a urinary metabolic phenotype associated with BP.Results: 29 structurally identified urinary metabolites covaried with systolic BP (SBP), after adjustment for demographic variables, and 18 metabolites with diastolic BP (DBP), with 16 metabolites overlapping between SBP and DBP. These included metabolites related to energy metabolism, renal function, diet and gut microbiota. After adjustment for medical and lifestyle covariates, 22/14 metabolites remained associated with SBP/DBP. Joint covariate-metabolite penalized regression models identified Body Mass Index, age and family history as most important contributors, with 14 metabolites, including gut microbial co-metabolites, also included in the model. Metabolites were mapped in a symbiotic metabolic reaction network, that includes reactions mediated by 3,344 commensal gut microbial species, to highlight affected pathways (Figure). Significant single nucleotide polymorphisms (SNPs) from genome-wide association studies on cardiometabolic risk factors were mapped to genes in this network. This revealed multiple sub
Barton W, Cronin O, GarciaPerez I, et al., 2021, The effects of sustained fitness improvement on the gut microbiome: A longitudinal, repeated measures case‐study approach, Translational Sports Medicine, Vol: 4, Pages: 174-192, ISSN: 2573-8488
The athlete gut microbiome differs from that of non‐athletes in its composition and metabolic function. Short‐term fitness improvement in sedentary adults does not replicate the microbiome characteristics of athletes. The objective of this study was to investigate whether sustained fitness improvement leads to pronounced alterations in the gut microbiome. This was achieved using a repeated‐measures, case‐study approach that examined the gut microbiome of two initially unfit volunteers undertaking progressive exercise training over a 6‐month period. Samples were collected every two weeks, and microbiome, metabolome, diet, body composition, and cardiorespiratory fitness data were recorded. Training culminated in both participants completing their respective goals (a marathon or Olympic‐distance triathlon) with improved body composition and fitness parameters. Increases in gut microbiota α‐diversity occurred with sustained training and fluctuations occurred in response to training events (eg, injury, illness, and training peaks). Participants’ BMI reduced during the study and was significantly associated with increased urinary measurements of N‐methyl nicotinate and hippurate, and decreased phenylacetylglutamine. These results suggest that sustained fitness improvements support alterations to gut microbiota and physiologically‐relevant metabolites. This study provides longitudinal analysis of the gut microbiome response to real‐world events during progressive fitness training, including intercurrent illness and injury.
Penney N, Barton W, Posma J, et al., 2020, Investigating the role of diet and exercise in gut microbe-hostcometabolism, mSystems, Vol: 5, Pages: 1-16, ISSN: 2379-5077
We investigated the individual and combined effects of diet and physical exercise on metabolism and the gut microbiome to establish how these lifestyle factors influence host-microbiome cometabolism. Urinary and fecal samples were collected from athletes and less active controls. Individuals were further classified according to an objective dietary assessment score of adherence to healthy dietary habits according to WHO guidelines, calculated from their proton nuclear magnetic resonance (1H-NMR) urinary profiles. Subsequent models were generated comparing extremes of dietary habits, exercise, and the combined effect of both. Differences in metabolic phenotypes and gut microbiome profiles between the two groups were assessed. Each of the models pertaining to diet healthiness, physical exercise, or a combination of both displayed a metabolic and functional microbial signature, with a significant proportion of the metabolites identified as discriminating between the various pairwise comparisons resulting from gut microbe-host cometabolism. Microbial diversity was associated with a combination of high adherence to healthy dietary habits and exercise and was correlated with a distinct array of microbially derived metabolites, including markers of proteolytic activity. Improved control of dietary confounders, through the use of an objective dietary assessment score, has uncovered further insights into the complex, multifactorial relationship between diet, exercise, the gut microbiome, and metabolism. Furthermore, the observation of higher proteolytic activity associated with higher microbial diversity indicates that increased microbial diversity may confer deleterious as well as beneficial effects on the host.
Petropoulou K, Salt LJ, Edwards CH, et al., 2020, A natural mutation in Pisum sativum L. (pea) alters starch assembly and improves glucose homeostasis in humans, Nature Food
Willis ND, Lloyd AJ, Xie L, et al., 2020, Design and characterisation of a randomized food intervention that mimics exposure to a typical UK diet to provide urine samples for identification and validation of metabolite biomarkers of food intake, Frontiers in Nutrition, Vol: 7, Pages: 1-16, ISSN: 2296-861X
Poor dietary choices are major risk factors for obesity and non-communicable diseases, which places an increasing burden on healthcare systems worldwide. To monitor the effectiveness of healthy eating guidelines and strategies, there is a need for objective measures of dietary intake in community settings. Metabolites derived from specific foods present in urine samples can provide objective biomarkers of food intake (BFIs). Whilst the majority of biomarker discovery/validation studies have investigated potential biomarkers for single foods only, this study considered the whole diet by using menus that delivered a wide range of foods in meals that emulated conventional UK eating patterns. Fifty-one healthy participants (range 19–77 years; 57% female) followed a uniquely designed, randomized controlled dietary intervention, and provided spot urine samples suitable for discovery of BFIs within a real-world context. Free-living participants prepared and consumed all foods and drinks in their own homes and were asked to follow the protocols for meal consumption and home urine sample collection. This study also assessed the robustness, and impact on data quality, of a minimally invasive urine collection protocol. Overall the study design was well-accepted by participants and concluded successfully without any drop outs. Compliance for urine collection, adherence to menu plans, and observance of recommended meal timings, was shown to be very high. Metabolome analysis using mass spectrometry coupled with data mining demonstrated that the study protocol was well-suited for BFI discovery and validation. Novel, putative biomarkers for an extended range of foods were identified including legumes, curry, strongly-heated products, and artificially sweetened, low calorie beverages. In conclusion, aspects of this study design would help to overcome several current challenges in the development of BFI technology. One specific attribute was the examination of BFI generalizabil
Beckmann M, Wilson T, Zubair H, et al., 2020, A standardized strategy for simultaneous quantification of urine metabolites to validate development of a biomarker panel allowing comprehensive assessment of dietary exposure., Molecular Nutrition and Food Research, Vol: 64, Pages: 1-15, ISSN: 1613-4125
SCOPE: Metabolites derived from individual foods found in human biofluids after consumption could provide objective measures of dietary intake. For comprehensive dietary assessment, quantification methods would need to manage the structurally diverse mixture of target metabolites present at a wide concentration range. METHODS & RESULTS: We developed a strategy for selection of candidate dietary exposure biomarkers, providing comprehensive coverage. An analytical method for 62 food biomarkers was validated by extensive analysis of chromatographic and ionization behaviour characteristics using triple quadrupole mass spectrometry. We used urine samples from two food intervention studies: one controlled, inpatient study (n = 19) and the other a free-living study where individuals (n = 15) were provided with food as a series of menu plans. As proof-of-principle, we demonstrated that the biomarker panel could discriminate between menu plans by detecting distinctive changes in the concentration in urine of targeted metabolites. We showed quantitative relationships between four biomarker concentrations in urine and dietary intake. CONCLUSIONS: We have demonstrated design concepts for an analytical strategy allowing simultaneous quantification of a comprehensive panel of chemically-diverse biomarkers of a wide range of commonly-consumed foods. We propose that integration of self-reported dietary recording tools with biomarker approaches will provide more robust assessment of dietary exposure. This article is protected by copyright. All rights reserved.
Garcia Perez I, Posma JM, Serrano Contreras JI, et al., 2020, Identifying unknown metabolites using NMR-based metabolic profiling techniques, Nature Protocols, Vol: 15, Pages: 2538-2567, ISSN: 1750-2799
Metabolic profiling of biological samples provides important insights into multiple physiological and pathological processes, but is hindered by a lack of automated annotation and standardised methods for structure elucidation of candidate disease biomarkers. Here, we describe a system for identifying molecular species derived from NMR spectroscopy based metabolic phenotyping studies, with detailed info on sample preparation, data acquisition, and data modelling. We provide eight different modular workflows to be followed in a recommended sequential order according to their level of difficulty. This multi-platform system involves the use of statistical spectroscopic tools such as STOCSY, STORM and RED-STORM to identify other signals in the NMR spectra relating to the same molecule. It also utilizes 2D-NMR spectroscopic analysis, separation and pre-concentration techniques, multiple hyphenated analytical platforms and data extraction from existing databases. The complete system, using all eight workflows, would take up to a month, as it includes multidimensional NMR experiments that require prolonged experiment times. However, easier identification cases using fewer steps would take two or three days. This approach to biomarker discovery is efficient, cost-effective and offers increased chemical space coverage of the metabolome, resulting in faster and more accurate assignment of NMR-generated biomarkers arising from metabolic phenotyping studies. Finally, it requires basic understanding of Matlab in order to perform statistical spectroscopic tools and analytical skills to perform Solid Phase Extraction, LC-fraction collection, LC-NMR-MS and 1D and 2D NMR experiments.
Posma JM, Garcia Perez I, Frost G, et al., 2020, Nutriome-metabolome relationships provide insights into dietary intake and metabolism, Nature Food, Vol: 1, Pages: 426-436, ISSN: 2662-1355
Dietary assessment traditionally relies on self-reported data which are often inaccurate and may result in erroneous diet-disease risk associations. We illustrate how urinary metabolic phenotyping can be used as alternative approach for obtaining information on dietary patterns. We used two multi-pass 24-hr dietary recalls, obtained on two occasions on average three weeks apart, paired with two 24-hr urine collections from 1,848 U.S. individuals; 67 nutrients influenced the urinary metabotype measured with ¹H-NMR spectroscopy characterized by 46 structurally identified metabolites. We investigated the stability of each metabolite over time and showed that the urinary metabolic profile is more stable within individuals than reported dietary patterns. The 46 metabolites accurately predicted healthy and unhealthy dietary patterns in a free-living U.S. cohort and replicated in an independent U.K. cohort. We mapped these metabolites into a host-microbial metabolic network to identify key pathways and functions. These data can be used in future studies to evaluate how this set of diet-derived, stable, measurable bioanalytical markers are associated with disease risk. This knowledge may give new insights into biological pathways that characterize the shift from a healthy to unhealthy metabolic phenotype and hence give entry points for prevention and intervention strategies.
Garcia Perez I, Posma JM, Chambers E, et al., 2020, Dietary metabotype modelling predicts individual responses to dietary interventions, Nature Food, Vol: 1, Pages: 355-364, ISSN: 2662-1355
Habitual consumption of poor quality diets is linked directly to risk factors for many non-communicable disease. This has resulted in the vast majority of countries globally and the World Health Organisation developing policies for healthy eating to reduce the prevalence of non communicable disease in the population. However, there is mounting evidence of variability in individual metabolic responses to any dietary intervention. We have developed a method for applying a pipeline for understanding inter-individual differences in response to diet, based on coupling data from highly-controlled dietary studies with deep metabolic phenotyping. In this feasibility study, we create an individual Dietary Metabotype Score (DMS) that embodies inter-individual variability in dietary response and captures consequent dynamic changes in concentrations of urinary metabolites. We find an inverse relationship between the DMS and blood glucose concentration. There is also a relationship between the DMS and urinary metabolic energy loss. Furthermore we employ a metabolic entropy approach to visualize individual and collective responses to dietary. Potentially, the DMS offers a method to target and to enhance dietary response at an individual level therefore reducing burden of non communicable diseases at a population level.
Allegretti JR, Kassam Z, Mullish BH, et al., 2020, Effects of fecal microbiota transplantation with oral capsules in obese patients, Clinical Gastroenterology and Hepatology, Vol: 18, Pages: 855-863.e2, ISSN: 1542-3565
Background & AimsStudies in mice have shown that the intestinal microbiota can contribute to obesity via the anorexigenic gut hormone glucagon-like peptide 1 (GLP1) and bile acids, which affect lipid metabolism. We performed a randomized, placebo-controlled pilot study of the effects of fecal microbiota transplantation (FMT) in obese, metabolically uncompromised patients.MethodsWe performed a double-blind study of 22 obese patients (body mass index [BMI] ≥ 35kg/m2) without a diagnosis of diabetes, non-alcoholic steatohepatitis, or metabolic syndrome. Participants were randomly assigned (1:1) to groups that received FMT by capsules (induction dose of 30 capsules at week 4 and maintenance dose of 12 capsules at week 8) or placebo capsules. FMT capsules were derived from a single, lean donor (BMI, 17.5 kg/m2). Patients were followed through week 26; the primary outcome was safety. Stool and serum samples were collected from patients at baseline and at weeks 1, 4, 6, 8 and 12 after administration of the first dose of FMT or placebo and analyzed by 16S RNA gene sequencing. Stool and serum samples were analyzed for metabolomics by liquid chromatography-mass spectrometry. Additional outcomes were change in area under the curve for GLP1 at week 12.ResultsWe observed no significant differences in adverse events between patients who received FMT vs placebo. There was no increase in the area under the curve of GLP1 in either group. Patients who received FMT had sustained shifts in microbiomes associated with obesity toward those of the donor (P<.001). Patients who received FMT had a sustained decrease in stool levels of taurocholic acid (P<.05), compared with baseline; bile acid profiles began to more closely resemble those of the donor. We did not observe significant changes in mean BMI at week 12 in either group.ConclusionsIn a placebo-controlled pilot study, we found that FMT capsules (derived from a lean donor) were safe but did not reduce BMI in obese metabol
Barbas-Bernardos C, Garcia-Perez I, Lorenzo MP, et al., 2020, Development and validation of a high performance liquid chromatography-tandem mass spectrometry method for the absolute analysis of 17 alpha D-amino acids in cooked meals, Journal of Chromatography A, Vol: 1611, Pages: 1-17, ISSN: 0021-9673
In the nutrition field, there is a lack of understanding about the impact that dietary chiral composition may have on health, especially regarding cooked meals. Chiral amino acids (AAs) are naturally present in food and their proportion may vary quite a lot. Besides, the D-amino acids (D-AAs) are present in very low concentration compared to L-AAs, so very sensitive methods are required for their accurate quantitation. Moreover, some of them have been described as indicators of quality and different food processes. In this research, we propose a robust method for the absolute quantitation and enantiomeric ratio of 17 D-AAs in cooked meals. The AAs were extracted from 1 g of the homogenised meal with methanol, derivatised with (S)-N-(4-nitrophenoxycarbonyl) phenylalanine methoxyethyl ester ((S)-NIFE) and analysed by RP-LC-MS/MS. The separation was carried out with an Acquity BEH C18 (100 mm x 2.1 mm, 1.7 µm) column at 70 ºC, with 10 mmol/L ammonium bicarbonate in water as eluent A and acetonitrile as eluent B at a 0.3 mL/min flow rate in gradient elution. The MS operated in positive electrospray ionisation method in multiple reaction monitoring (MRM) mode. Isotopically labelled AAs were used as internal standards for the quantitation. The method was validated for 17 D-AAs in the cooked food samples in terms of specificity, linearity, precision, accuracy, matrix effect and stability. LLOQ are 2.0 ng/mL for most of them. Additionally, linearity was also studied for L-AAs. After optimization and validation, the method was applied to real breakfast, lunch and dinner samples of cooked meals (n = 18) that were part of a diet with a very high concordance with WHO dietary guidelines. Level of concentration of major and minor D-AAs have been described per total daily intake and within each of the three main meals. This method can be used for quality control purposes as well as to investigate the role of chiral composition in food and clinical outcomes.
O'Donovan CM, Madigan SM, Garcia-Perez I, et al., 2020, Distinct microbiome composition and metabolome exists across subgroups of elite Irish athletes, Journal of Science and Medicine in Sport, Vol: 23, Pages: 63-68, ISSN: 1440-2440
ObjectivesThe gut microbiome has begun to be characterised in athlete groups, albeit, to date, only across a subset of sports. This study aimed to determine if the gut microbiome and metabolome differed across sports classification groups (SCGs) among elite Irish athletes, many of whom were participating in the 2016 Summer Olympics.MethodsFaecal and urine samples were collected from 37 international level athletes. Faecal samples were prepared for shotgun metagenomic sequencing and faecal and urine samples underwent metabolomic profiling.ResultsDifferences were observed in the composition and functional capacity of the gut microbiome of athletes across SCGs. The microbiomes of athletes participating in sports with a high dynamic component were the most distinct compositionally (greater differences in proportions of species), while those of athletes participating in sports with high dynamic and static components were the most functionally distinct (greater differences in functional potential). Additionally, both microbial (faecal) and human (urine) derived metabolites were found to vary between SCGs. In particular cis-aconitate, succinic acid and lactate, in urine samples, and creatinine, in faeces, were found to be significantly different between groups. These differences were evident despite the absence of significant differences in diet, as determined using food frequency questionnaires, which were translated into nutrient intake values using FETA.ConclusionsDifferences in the gut microbiome and metabolome between groups, in the absence of dietary changes, indicates a role for training load or type as a contributory factor. Further exploration of this hypothesis has the potential to benefit athletes, aspiring athletes and the general public.
Kundu P, Lee HU, Garcia-Perez I, et al., 2019, Neurogenesis and prolongevity signaling in young germ-free mice transplanted with the gut microbiota of old mice., Science Translational Medicine, Vol: 11, Pages: 1-13, ISSN: 1946-6234
The gut microbiota evolves as the host ages, yet the effects of these microbial changes on host physiology and energy homeostasis are poorly understood. To investigate these potential effects, we transplanted the gut microbiota of old or young mice into young germ-free recipient mice. Both groups showed similar weight gain and skeletal muscle mass, but germ-free mice receiving a gut microbiota transplant from old donor mice unexpectedly showed increased neurogenesis in the hippocampus of the brain and increased intestinal growth. Metagenomic analysis revealed age-sensitive enrichment in butyrate-producing microbes in young germ-free mice transplanted with the gut microbiota of old donor mice. The higher concentration of gut microbiota-derived butyrate in these young transplanted mice was associated with an increase in the pleiotropic and prolongevity hormone fibroblast growth factor 21 (FGF21). An increase in FGF21 correlated with increased AMPK and SIRT-1 activation and reduced mTOR signaling. Young germ-free mice treated with exogenous sodium butyrate recapitulated the prolongevity phenotype observed in young germ-free mice receiving a gut microbiota transplant from old donor mice. These results suggest that gut microbiota transplants from aged hosts conferred beneficial effects in responsive young recipients.
Wilson T, Garcia-Perez I, Posma JM, et al., 2019, Spot and cumulative urine samples are suitable replacements for 24-hour urine collections for objective measures of dietary exposure in adults using metabolite biomarkers, Journal of Nutrition, Vol: 149, Pages: 1692-1700, ISSN: 0022-3166
BACKGROUND: Measurement of multiple food intake exposure biomarkers in urine may offer an objective method for monitoring diet. The potential of spot and cumulative urine samples that have reduced burden on participants as replacements for 24-h urine collections has not been evaluated. OBJECTIVE: The aim of this study was to determine the utility of spot and cumulative urine samples for classifying the metabolic profiles of people according to dietary intake when compared with 24-h urine collections in a controlled dietary intervention study. METHODS: Nineteen healthy individuals (10 male, 9 female, aged 21-65 y, BMI 20-35 kg/m2) each consumed 4 distinctly different diets, each for 1 wk. Spot urine samples were collected ∼2 h post meals on 3 intervention days/wk. Cumulative urine samples were collected daily over 3 separate temporal periods. A 24-h urine collection was created by combining the 3 cumulative urine samples. Urine samples were analyzed with metabolite fingerprinting by both high-resolution flow infusion electrospray mass spectrometry (FIE-HRMS) and proton nuclear magnetic resonance spectroscopy (1H-NMR). Concentrations of dietary intake biomarkers were measured with liquid chromatography triple quadrupole mass spectrometry and by integration of 1H-NMR data. RESULTS: Cross-validation modeling with 1H-NMR and FIE-HRMS data demonstrated the power of spot and cumulative urine samples in predicting dietary patterns in 24-h urine collections. Particularly, there was no significant loss of information when post-dinner (PD) spot or overnight cumulative samples were substituted for 24-h urine collections (classification accuracies of 0.891 and 0.938, respectively). Quantitative analysis of urine samples also demonstrated the relation between PD spot samples and 24-h urines for dietary exposure biomarkers. CONCLUSIONS: We conclude that PD spot urine samples are suitable replacements for 24-h urine collections. Alternatively, cumulative samples collected overn
Allegretti JR, Mullish B, Hurtado J, et al., 2019, Short chain fatty acid profiles are altered by fecal microbiota transplantation for the treatment of inflammatory bowel disease and recurrent clostridioides difficile infection, American Journal of Gastroenterology, Vol: 114, Pages: S484-S485, ISSN: 0002-9270
Lahiri S, Kim H, Garcia-Perez I, et al., 2019, The gut microbiota influences skeletal muscle mass and function in mice, Science Translational Medicine, Vol: 11, ISSN: 1946-6234
The functional interactions between the gut microbiota and the host are important for host physiology, homeostasis, and sustained health. We compared the skeletal muscle of germ-free mice that lacked a gut microbiota to the skeletal muscle of pathogen-free mice that had a gut microbiota. Compared to pathogen-free mouse skeletal muscle, germ-free mouse skeletal muscle showed atrophy, decreased expression of insulin-like growth factor 1, and reduced transcription of genes associated with skeletal muscle growth and mitochondrial function. Nuclear magnetic resonance spectrometry analysis of skeletal muscle, liver, and serum from germ-free mice revealed multiple changes in the amounts of amino acids, including glycine and alanine, compared to pathogen-free mice. Germ-free mice also showed reduced serum choline, the precursor of acetylcholine, the key neurotransmitter that signals between muscle and nerve at neuromuscular junctions. Reduced expression of genes encoding Rapsyn and Lrp4, two proteins important for neuromuscular junction assembly and function, was also observed in skeletal muscle from germ-free mice compared to pathogen-free mice. Transplanting the gut microbiota from pathogen-free mice into germ-free mice resulted in an increase in skeletal muscle mass, a reduction in muscle atrophy markers, improved oxidative metabolic capacity of the muscle, and elevated expression of the neuromuscular junction assembly genes <jats:italic>Rapsyn</jats:italic> and <jats:italic>Lrp4</jats:italic>. Treating germ-free mice with short-chain fatty acids (microbial metabolites) partly reversed skeletal muscle impairments. Our results suggest a role for the gut microbiota in regulating skeletal muscle mass and function in mice.</jats:p>
Ek A, Nystrom CD, Chirita-Emandi A, et al., 2019, A randomized controlled trial for overweight and obesity in preschoolers: the More and Less Europe study- an intervention within the STOP project, BMC Public Health, Vol: 19, Pages: 1-13, ISSN: 1471-2458
BackgroundChildhood overweight and obesity is a serious public health issue with an increase being observed in preschool-aged children. Treating childhood obesity is difficult and few countries use standardized treatments. Therefore, there is a need to find effective approaches that are feasible for both health care providers and families. Thus, the overall aim of this study is to assess the acceptance and effectiveness of a parent support program (the More and Less, ML) for the management of overweight and obesity followed by a mobile health (mHealth) program (the MINISTOP application) in a socially diverse population of families.Methods/designA two-arm, parallel design randomized controlled trial in 300 2-to 6-year-old children with overweight and obesity from Romania, Spain and Sweden (n = 100 from each). Following baseline assessments children are randomized into the intervention or control group in a 1:1 ratio. The intervention, the ML program, consists of 10-weekly group sessions which focus on evidence-based parenting practices, followed by the previously validated MINISTOP application for 6-months to support healthy eating and physical activity behaviors. The primary outcome is change in body mass index (BMI) z-score after 9-months and secondary outcomes include: waist circumference, eating behavior (Child Eating Behavior Questionnaire), parenting behavior (Comprehensive Feeding Practices Questionnaire), physical activity (ActiGraph wGT3x-BT), dietary patterns (based on metabolic markers from urine and 24 h dietary recalls), epigenetic and gut hormones (fasting blood samples), and the overall acceptance of the overweight and obesity management in young children (semi-structured interviews). Outcomes are measured at baseline and after: 10-weeks (only BMI z-score, waist circumference), 9-months (all outcomes), 15- and 21-months (all outcomes except physical activity, dietary patterns, epigenetics and gut hormones) post-baseline.DiscussionT
Chambers E, Byrne C, Morrison D, et al., 2019, Dietary supplementation with inulin-propionate ester or inulin improves insulin sensitivity in adults with overweight and obesity with distinct effects on the gut microbiota, plasma metabolome and systemic inflammatory responses: a randomised cross-over trial, Gut, Vol: 68, Pages: 1430-1438, ISSN: 0017-5749
Objective: To investigate the underlying mechanisms behind changes in glucose homeostasis with delivery of propionate to the human colon by comprehensive and coordinated analysis of gut bacterial composition, plasma metabolome and immune responses.Design: Twelve non-diabetic adults with overweight and obesity received 20g/day of inulin-propionate ester (IPE), designed to selectively deliver propionate to the colon, a high-fermentable fibre control (inulin) and a low-fermentable fibre control (cellulose) in a randomised, double-blind, placebo controlled, crossover design. Outcome measurements of metabolic responses, inflammatory markers and gut bacterial composition were analysed at the end of each 42-day supplementation period.Results: Both IPE and inulin supplementation improved insulin resistance compared to cellulose supplementation, measured by homeostatic model assessment (HOMA) 2 (Mean±SEM 1.23±0.17 IPE vs. 1.59±0.17 cellulose, P=0.001; 1.17±0.15 inulin vs. 1.59±0.17 cellulose, P=0.009), with no differences between IPE and inulin (P=0.272). Fasting insulin was only associated positively with plasma tyrosine and negatively with plasma glycine following inulin supplementation. IPE supplementation decreased pro-inflammatory IL-8 levels compared to cellulose, whilst inulin had no impact on the systemic inflammatory markers studied. Inulin promoted changes in gut bacterial populations at the class level (increased Actinobacteria and decreased Clostridia) and order level (decreased Clostridales) compared to cellulose, with small differences at the species level observed between IPE and cellulose. Conclusion: These data demonstrate a distinctive physiological impact of raising colonic propionate delivery in humans, as improvements in insulin sensitivity promoted by IPE and inulin were accompanied with different effects on the plasma metabolome, gut bacterial populations and markers of systemic inflammation.
Lloyd AJ, Willis ND, Wilson T, et al., 2019, Developing a food exposure and urine sampling strategy for dietary exposure biomarker validation in free-living individuals, Molecular Nutrition and Food Research, Vol: 63, Pages: 1-9, ISSN: 1613-4125
SCOPE: Dietary choices modulate the risk of chronic diseases and improving diet is a central component of public health strategies. Food-derived metabolites present in urine could provide objective biomarkers of dietary exposure. To assist biomarker validation we aimed to develop a food intervention strategy mimicking a typical annual diet over a short period of time and assessed urine sampling protocols potentially suitable for future deployment of biomarker technology in free-living populations. METHODS AND RESULTS: Six different menu plans representing comprehensively a typical UK annual diet that were split into two dietary experimental periods. Free-living adult participants (n = 15 and n = 36, respectively) were provided with all their food, as a series of menu plans, over a period of 3 consecutive days. Multiple spot urine samples were collected and stored at home. CONCLUSION: We established a successful food exposure strategy following a conventional UK eating pattern, which was suitable for biomarker validation in free-living individuals. The urine sampling procedure was acceptable for volunteers and delivered samples suitable for biomarker quantification. Our study design provides scope for validation of existing biomarker candidates and potentially for discovery of new biomarker-leads and should help inform the future deployment of biomarker technology for habitual dietary exposure measurement.
Lloyd AJ, Willis ND, Wilson T, et al., 2019, Addressing the pitfalls when designing intervention studies to discover and validate biomarkers of habitual dietary intake, Metabolomics, Vol: 15, ISSN: 1573-3882
IntroductionDietary exposure monitoring within populations is reliant on self-reported measures such as Food Frequency Questionnaires and diet diaries. These methods often contain inaccurate information due to participant misreporting, non-compliance and bias. Urinary metabolites derived from individual foods could provide additional objective indicators of dietary exposure. For biomarker approaches to have utility it is essential that they cover a wide-range of commonly consumed foods and the methodology works in a real-world environment.ObjectivesTo test that the methodology works in a real-world environment and to consider the impact of the major sources of likely variance; particularly complex meals, different food formulations, processing and cooking methods, as well as the dynamics of biomarker duration in the body.MethodsWe designed and tested a dietary exposure biomarker discovery and validation strategy based on a food intervention study involving free-living individuals preparing meals and collecting urine samples at home. Two experimental periods were built around three consecutive day menu plans where all foods and drinks were provided (n = 15 and n = 36).ResultsThe experimental design was validated by confirming known consumption biomarkers in urinary samples after the first menu plan. We tested biomarker performance with different food formulations and processing methods involving meat, wholegrain, fruits and vegetables.ConclusionIt was demonstrated that spot urine samples, together with robust dietary biomarkers, despite major sources of variance, could be used successfully for dietary exposure monitoring in large epidemiological studies.
Churchward MA, Michaud ER, Blanco JM, et al., 2019, Sa1924 – Effect of short chain fatty acids on gut-brain axis using a microglial cell model, Gastroenterology, Vol: 156, Pages: S-455-S-455, ISSN: 0016-5085
Byrne C, Chambers E, Brignardello J, et al., 2019, Effects of inulin propionate ester incorporated into palatable food products on appetite and resting energy expenditure: a randomised crossover study, Nutrients, Vol: 11, ISSN: 2072-6643
Supplementation with inulin-propionate ester (IPE), which delivers propionate to the colon, suppresses ad libitum energy intake and stimulates the release of satiety hormones acutely in humans, and prevents weight gain. In order to determine whether IPE remains effective when incorporated into food products (FP), IPE needs to be added to a widely accepted food system. A bread roll and fruit smoothie were produced. Twenty-one healthy overweight and obese humans participated. Participants attended an acclimatisation visit and a control visit where they consumed un-supplemented food products (FP). Participants then consumed supplemented-FP, containing 10 g/d inulin or IPE for six days followed by a post-supplementation visit in a randomised crossover design. On study visits, supplemented-FP were consumed for the seventh time and ad libitum energy intake was assessed 420 min later. Blood samples were collected to assess hormones and metabolites. Resting energy expenditure (REE) was measured using indirect calorimetry. Taste and appearance ratings were similar between FP. Ad libitum energy intake was significantly different between treatments, due to a decreased intake following IPE-FP. These observations were not related to changes in blood hormones and metabolites. There was an increase in REE following IPE-FP. However, this effect was lost after correcting for changes in fat free mass. Our results suggest that IPE suppresses appetite and may alter REE following its incorporation into palatable food products.
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