Incorporating standardised drift-tube ion mobility to enhance non-targeted assessment of the wine metabolome (LC×IM-MS)

Liquid chromatography with drift-tube ion mobility spectrometry-mass spectrometry (LCxIM-MS) is emerging as a powerful addition to existing LC-MS workflows for addressing a diverse range of metabolomics-related questions [1,2]. Importantly, excellent precision under repeatability and reproducibility conditions of drift-tube IM separations [3] supports the development of non-targeted approaches for complex metabolome assessment such as wine characterisation [4]. In this work, fundamentals of this new analytical metabolomics approach are introduced and application to the analysis of 90 authentic red and white wine samples originating from Macedonia is presented. Following measurements, intersample alignment of metabolites using non-targeted extraction and three-dimensional alignment of molecular features (retention time, collision cross section, and high-resolution mass spectra) provides confidence for metabolite identity confirmation. Applying a fingerprinting metabolomics workflow allows statistical assessment of the influence of geographic region, variety, and age. This approach is a state-of-the-art tool to assess wine chemodiversity and is particularly beneficial for the discovery of wine biomarkers and establishing product authenticity based on development of fingerprint libraries

The impact of sequence database choice on metaproteomic results in gut microbiota studies

Background: Elucidating the role of gut microbiota in physiological and pathological processes has recently emerged as a key research aim in life sciences. In this respect, metaproteomics, the study of the whole protein complement of a microbial community, can provide a unique contribution by revealing which functions are actually being expressed by specific microbial taxa. However, its wide application to gut microbiota research has been hindered by challenges in data analysis, especially related to the choice of the proper sequence databases for protein identification. Results: Here, we present a systematic investigation of variables concerning database construction and annotation and evaluate their impact on human and mouse gut metaproteomic results. We found that both publicly available and experimental metagenomic databases lead to the identification of unique peptide assortments, suggesting parallel database searches as a mean to gain more complete information. In particular, the contribution of experimental metagenomic databases was revealed to be mandatory when dealing with mouse samples. Moreover, the use of a "merged" database, containing all metagenomic sequences from the population under study, was found to be generally preferable over the use of sample-matched databases. We also observed that taxonomic and functional results are strongly database-dependent, in particular when analyzing the mouse gut microbiota. As a striking example, the Firmicutes/Bacteroidetes ratio varied up to tenfold depending on the database used. Finally, assembling reads into longer contigs provided significant advantages in terms of functional annotation yields. Conclusions: This study contributes to identify host- and database-specific biases which need to be taken into account in a metaproteomic experiment, providing meaningful insights on how to design gut microbiota studies and to perform metaproteomic data analysis. In particular, the use of multiple databases and annotation tools has to be encouraged, even though this requires appropriate bioinformatic resources

Metabolic dysfunction-associated steatotic liver disease:A wide-angled perspective on a multifaceted problem

In dit proefschrift is metabole dysfunctie-geassocieerde steatotische leverziekte (MASLD) onderzocht, opgedeeld in drie delen:Deel 1 omvat een MRI-onderzoek naar vetstapeling in de lever en pancreas, en een genoombrede associatiestudie in de Amsterdamse multi-etnische populatie, waarbij een relatie tussen het gen MRC1 en niet-invasieve leverfibrosetesten wordt gevonden. Dit gen vertoont variaties tussen etnische groepen, wat wijst op een rol van MRC1 in de bestaande verschillen in MASLD tussen bevolkingsgroepen van verschillende afkomst.In deel 2 is gericht op nieuwe niet-invasieve levertesten van fibrosevorming in mensen met MASLD. Ten eerste een systematische review van de marker Pro-C3 voor het detecteren van fibrose, en ten tweede een onderzoek naar een nieuw niet-invasief biomarkerpanel, van ontdekking in muisstudies tot bevestiging in humane cohorten.Deel 3 van het proefschrift beschrijft de potentie van het darmmicrobioom om MASLD te beïnvloeden. Een fecestransplantatiestudie toont aan dat het manipuleren van het darmmicrobioom leidt tot veranderingen in circulerende metabolieten en lever-DNA-methylatie. Daarnaast beschrijft een muisonderzoek het effect van de boterzuurproducerende bacterie A. soehngenii op de ernst van MASLD, waarbij toediening ervan de suikerhuishouding verbeterde zonder verbetering van de leverhistologie.Gezamenlijk leveren de studies die in dit proefschrift beschreven zijn waardevolle inzichten in de complexiteit van MASLD en bieden ze verschillende potentiële mogelijkheden om de zorg voor mensen met MASLD te verbeteren door middel van genetische, metabole en microbioom-gerichte benaderingen

Exploring gut microbiome – host interactions in the extremes of health and disease

Introduction: Multi ‘omics analyses, including metabonomic and metagenomic profiling techniques, have enabled new insights into systems biology over the past decade. Using two extremes of a continuum between health and disease – elite athletes and obese patients undergoing bariatric surgery – the work in this thesis aims to apply metabolic phenotyping to further understand the impact of exercise, diet and obesity on human metabolism. Furthermore, through combinatorial analysis of metabonomic and gut microbiome data sets, host – gut microbiome co-metabolism and its influence on health is explored in these two extreme populations. Methods: Biofluids were collected from three cohorts: i) elite athletes and age and sex matched controls, ii) healthy individuals before and after a high protein diet, exercise regime or both, and iii) obese subjects pre and post bariatric surgery. Multiple analytical platforms were utilised for metabolic profiling including 1H-NMR spectroscopy, UPLC-MS and GC-MS. Gut microbiome analysis was performed using next generation metagenomic sequencing. After pre-processing the metabonomic and metagenomic data; univariate, unsupervised and supervised multivariate analyses were performed as well as gut microbiome-metabolite association studies. Results: Distinct metabolic and microbial phenotypes existed between both athletes and controls and between obese patients before and after bariatric surgery. Discriminatory metabolites higher in athletes include metabolites associated with muscle turnover, vitamins and recovery supplements, a high protein diet and those derived from gut microbes. Interestingly, increased bacterial diversity seen in athletes correlated with a specific subset of metabolites. Similarly, bariatric surgery resulted in large changes to circulating metabolites. A number of these metabolites were linked to changes in the gut microbiome, including bile acids, short-chain fatty acids and amino acids. Conclusion: This thesis extends existing knowledge of the gut microbiome’s influence on human health through small molecule signalling. Mechanistic studies are now needed to establish causal links between gut microbes, changes to circulating metabolites and disease status.Open Acces

Genetic mapping of metabolic biomarkers of cardiometabolic diseases

Cardiometabolic disorders (CMDs) are a major public health problem worldwide. The main goal of this thesis is to characterize the genetic architecture of CMD-related metabolites in a Lebanese cohort. In order to maximise the extraction of meaningful biological information from this dataset, an important part of this thesis focuses on the evaluation and subsequent improvement of the standard methods currently used for molecular epidemiology studies. First, I describe MetaboSignal, a novel network-based approach to explore the genetic regulation of the metabolome. Second, I comprehensively compare the recovery of metabolic information in the different 1H NMR strategies routinely used for metabolic profiling of plasma (standard 1D, spin-echo and JRES). Third, I describe a new method for dimensionality reduction of 1H NMR datasets prior to statistical modelling. Finally, I use all this methodological knowledge to search for molecular biomarkers of CMDs in a Lebanese population. Metabolome-wide association analyses identified a number of metabolites associated with CMDs, as well as several associations involving N-glycan units from acute-phase glycoproteins. Genetic mapping of these metabolites validated previously reported gene-metabolite associations, and revealed two novel loci associated with CMD-related metabolites. Collectively, this work contributes to the ongoing efforts to characterize the molecular mechanisms underlying complex human diseases.Open Acces

Toward a Standardized Strategy of Clinical Metabolomics for the Advancement of Precision Medicine

Despite the tremendous success, pitfalls have been observed in every step of a clinical metabolomics workflow, which impedes the internal validity of the study. Furthermore, the demand for logistics, instrumentations, and computational resources for metabolic phenotyping studies has far exceeded our expectations. In this conceptual review, we will cover inclusive barriers of a metabolomics-based clinical study and suggest potential solutions in the hope of enhancing study robustness, usability, and transferability. The importance of quality assurance and quality control procedures is discussed, followed by a practical rule containing five phases, including two additional "pre-pre-" and "post-post-" analytical steps. Besides, we will elucidate the potential involvement of machine learning and demonstrate that the need for automated data mining algorithms to improve the quality of future research is undeniable. Consequently, we propose a comprehensive metabolomics framework, along with an appropriate checklist refined from current guidelines and our previously published assessment, in the attempt to accurately translate achievements in metabolomics into clinical and epidemiological research. Furthermore, the integration of multifaceted multi-omics approaches with metabolomics as the pillar member is in urgent need. When combining with other social or nutritional factors, we can gather complete omics profiles for a particular disease. Our discussion reflects the current obstacles and potential solutions toward the progressing trend of utilizing metabolomics in clinical research to create the next-generation healthcare system.11Ysciescopu

Nutritional modulation of metabolic phenotypes

Diet and other lifestyle factors play a critical role in the risk of developing many diseases. Metabolic profiles contain a wealth of biochemical and physiological information and are influenced by various factors such as gender, age, BMI or genetic background. Diet is an important factor, and long-term dietary habits as well as short-term food challenges influence the metabolic phenotype. Metabolic profiling technology can be used to discover novel single or combination biomarkers of food intake. To aid personalised healthy lifestyle recommendations, it is necessary to characterise the metabolic phenotype of individuals and to establish the extent to which we can beneficially influence this phenotype by nutritional intervention. This thesis aims to evaluate metabonomics as a tool for systematically detecting metabolites related to inter-individual and food-related differences. In order to address these aims a nutrition study was undertaken, where individuals followed a strict diet regime consuming a standard diet including specific food challenges, spot urine collections were made throughout the study period. 1H NMR spectroscopy was performed to generate urinary metabolic profiles, which were subsequently analysed and interpreted using multivariate mathematical modelling methods. Clear metabolic signatures pertaining to the consumption of specific dietary components and ‘biomarker’ metabolites associated with particular foods were extracted. Further validation of a potential biomarker was undertaken interrogating a large-scale epidemiologic dataset, the INTERMAP Study. Inter-individual variation in the metabolic profile was observed, both in relation to differences in response to food ingestion and metabolic differences independent from immediate food ingestion. Among these alterations were metabolites originating from gut microbial-mammalian co-metabolism. The influence of the gut microbiota on the metabolic phenotype and obesity was further investigated using microbially modulated murine models. This thesis characterises the effects of the interaction of diet and microbial metabolism on the metabolic phenotype and provides a template for assessing complex dietary interventions with respect to beneficially modulating metabolism

EVALUATING THE MICROBIOME TO BOOST RECOVERY FROM STROKE: THE EMBRS STUDY

Accumulating evidence suggests that gut microbes modulate brain plasticity via the bidirectional gut-brain axis and may play a role in stroke rehabilitation. A severely imbalanced microbial community has been shown to occur following stroke, causing a systemic flood of neuro- and immunomodulatory substances due to increased gut permeability and decreased gut motility. Here we measure post-stroke increased gut dysbiosis and how it correlates with gut permeability and subsequent cognitive impairment. We recruited 12 participants with acute stroke, 12 healthy control participants, and 18 participants who had risk factors for stroke, but had not had a stroke. We measured the gut microbiome with whole shotgun sequencing on stool samples. We measured cognitive and emotional health with MRI imaging and the NIH toolbox. We normalized all variables and used linear regression methods to identify gut microbial levels associations with cognitive and emotional assessments. Beta diversity analysis revealed that the bacteria populations of the stroke group were statistically dissimilar from the risk factors and healthy control groups. Relative abundance analysis revealed notable decreases in butyrate-producing microbial taxa. The stroke group had higher levels of the leaky gut marker alpha-1-antitrypsin than the control groups, and roseburia species were negatively correlated with alpha-1-antitrypsin. Several Actinobacteria species were associated with cerebral blood flow and white matter integrity in areas of the brain responsible for language, learning, and memory. Stroke participants scored lower on the picture vocabulary and list sorting tests than those in the control groups. Stroke participants who had higher levels of roseburia performed better on the picture vocabulary task. We found that microbial communities are disrupted in a stroke population. Many of the disrupted bacteria have previously been reported to have correlates to health and disease. This preparatory study will lay the foundation for the development of therapeutics targeting the gut following stroke

Multi-omics biomarkers of metabolic homeostasis of risk factors associated to non-communicable diseases

Les malalties no transmissibles, com l'obesitat, la síndrome metabòlica, les malalties cardiovasculars, el càncer i les malalties neurodegeneratives, es consideren malalties multifactorials. Per aquesta raó, s'ha proposat que l'aparició d’aquestes malalties es deu a un desequilibri de processos globals. El seguiment d'aquests processos obre la porta a la possibilitat de modular-los i, per tant, prevenir-los mitjançant el disseny d'intervencions/tractaments personalitzats més precisos. No obstant això, els biomarcadors actuals no tenen la capacitat d'avaluar les alteracions primerenques que podrien conduir al desenvolupament de la malaltia, la qual cosa posa de manifest la necessitat de definir nous biomarcadors. Per tant, en el present treball es presenta una signatura metabòlica característica de processos específics obtinguda mitjançant l'ús de tecnologies òmiques: disfunció de carbohidrats, hiperlipèmia, hipertensió i dysbiosis intestinal, com a representatius de l'estrès metabòlic; l'estrès inflamatori; l'estrès oxidatiu i l'estrès psicològic. Per això, s'han desenvolupat diferents models animals i s'ha avaluat el perfil metabòlic dels diferents factors de risc d'interès en plasma i orina. Els resultats indiquen que els lípids i els intermediaris del cicle del TCA són els metabòlits més prometedors del perfil metabòlic. En tots els factors de risc, els diacilglicerols (DG) són els biomarcadors lipídics amb major impacte: en concret, el DG 36:4 i el DG 34:2 vinculen els factors de risc amb el metabolisme de l'àcid araquidònic. En inflamació, estrès oxidatiu i psicològic, l'altre protagonista és el cicle del TCA a causa del seu paper clau en el mitocondri amb l'alfa-cetoglutarat com l'intermediari més prometedor. En conseqüència, el perfil metabòlic presentat és una eina potencial per al seguiment dels factors de risc i podria obrir una finestra per a orientar l'aparició de malalties i intentar prevenir-les i tractar-les.Las enfermedades no transmisibles, como la obesidad, el síndrome metabólico, las enfermedades cardiovasculares, el cáncer y las enfermedades neurodegenerativas, se consideran enfermedades multifactoriales. Por esta razón, se ha propuesto que la aparición de estas enfermedades se debe a un desequilibrio de procesos globales. El seguimiento de estos procesos abre la puerta a la posibilidad de modularlos y, por lo tanto, prevenirlos mediante el diseño de intervenciones/tratamientos personalizados más precisos. Sin embargo, los biomarcadores actuales no tienen la capacidad de evaluar las alteraciones tempranas que podrían conducir al desarrollo de la enfermedad, lo que pone de manifiesto la necesidad de definir nuevos biomarcadores. Por lo tanto, en el presente trabajo se presenta una firma metabólica característica de procesos específicos obtenida mediante el uso de tecnologías ómicas: disfunción de carbohidratos, hiperlipidemia, hipertensión y disbiosis intestinal, como representativos del estrés metabólico; el estrés inflamatorio; el estrés oxidativo y el estrés psicológico. Para ello se han desarrollado diferentes modelos animales y se ha evaluado el perfil metabólico de los diferentes factores de riesgo de interés en plasma y orina. Los resultados indicaron que los lípidos y los intermediarios del ciclo del TCA son los metabolitos más prometedores del perfil metabólico. En todos los factores de riesgo, los diacilgliceroles (DG) son el biomarcador lipídico con mayor impacto: en concreto, el DG 36:4 y el DG 34:2 vinculan los factores de riesgo con el metabolismo del ácido araquidónico. En inflamación, estrés oxidativo y psicológico, el otro protagonista es el ciclo del TCA debido a su papel clave en la mitocondria con el alfa-cetoglutarato como el intermediario más prometedor. En consecuencia, el perfil metabólico presentado es una herramienta potencial para el seguimiento de los factores de riesgo y podría abrir una ventana para orientar la aparición de enfermedades e intentar prevenirlas y tratarlas.Non-communicable diseases, such as obesity, metabolic syndrome, cardiovascular diseases, cancer and neurodegenerative diseases, are considered multifactorial diseases. For this reason, it has been proposed that the occurrence of these diseases is due to an imbalance of overarching processes (i.e., metabolic, inflammatory, oxidative, and psychological stress). Monitoring these overarching processes opens the door to the possibility of modulating them, and thus preventing the occurrence of different process through the design of more precise personalised interventions or treatments. However, current biomarkers of disease cannot assess early alterations that could lead to the development of disease, highlighting the need to define new biomarkers. Thus, the present work presents a characteristic metabolic signature for the detection of specific processes using omic technologies: carbohydrate dysfunction, hyperlipidaemia, hypertension and intestinal dysbiosis, as representative of metabolic stress; inflammatory stress; oxidative stress and psychological stress. For this purpose, different animal models have been developed and the metabolic profile in plasma and urine has been evaluated in the different risk factors of interest. The results indicated that lipids and TCA cycle intermediates are the most promising metabolites of the metabolic profile. In all the risk factors, diacylglycerols (DG) are the lipidic biomarker with the greatest impact on metabolic profiles: specifically, DG 36:4 and DG 34:2 linking risk factors to arachidonic acid metabolism. In inflammation, oxidative and psychological stress, the other protagonist is the TCA cycle due to its multiple roles in mitochondrial metabolism: being alpha-ketoglutarate one of the most promising intermediate. In consequence, the presented metabolic profile is a potential tool for the monitoring of risk factors and could open a window to target the onset of diseases and try to prevent and treat them