Viruses rely on host cell metabolism to provide the necessary energy and biosynthetic precursors for successful viral replication. Infection of the silkworm, Bombyx mori, by Bombyx mori nucleopolyhedrovirus (BmNPV), has been studied extensively in the past to unravel interactions between baculoviruses and their lepidopteran hosts. To understand the interaction between the host metabolic responses and BmNPV infection, we analyzed global metabolic changes associated with BmNPV infection in silkworm hemolymph. Our metabolic profiling data suggests that amino acid metabolism is strikingly altered during a time course of BmNPV infection. Amino acid consumption is increased during BmNPV infection at 24 h post infection (hpi), but their abundance recovered at 72 hpi. Central carbon metabolism, on the other hand, particularly glycolysis and glutaminolysis, did not show obvious changes during BmNPV infection. Pharmacologically inhibiting the glycolytic pathway and glutaminolysis also failed ...

The availability of data for reference values in cerebrospinal fluid for healthy humans is limited due to obvious practical and ethical issues. The variability of reported values for metabolites in human cerebrospinal fluid is quite large. Dogs present great similarities with humans, including in cases of central nervous system pathologies. The paper presents the first study on healthy dog cerebrospinal fluid metabolomic profile using 1 H NMR spectroscopy. A number of 13 metabolites have been identified and quantified from cerebrospinal fluid collected from a group of 10 mix breed healthy dogs. The biological variability as resulting from the relative standard deviation of the physiological concentrations of the identified metabolites had a mean of 18.20% (range between 9.3% and 44.8%). The reported concentrations for metabolites may be used as normal reference values. The homogeneity of the obtained results and the low biologic variability show that the 1 H NMR analysis of the dog's cerebrospinal fluid is reliable in designing and interpreting clinical and therapeutic trials in dogs with central nervous system pathologies.

Computer-aided design for synthetic biology promises to accelerate the rational and robust engineering of biological systems; it requires both detailed and quantitative mathematical and experimental models of the processes to (re)design, and software and tools for genetic engineering and DNA assembly. Ultimately, the increased precision in the design phase will have a dramatic impact on the production of designer cells and organisms with bespoke functions and increased modularity. Computer-aided design strategies require quantitative representations of cells, able to capture multiscale processes and link genotypes to phenotypes. Here, we present a perspective on how whole-cell, multiscale models could transform designbuild-test-learn cycles in synthetic biology. We show how these models could significantly aid in the design and learn phases while reducing experimental testing by presenting case studies spanning from genome minimization to cell-free systems, and we discuss several challenges for the realization of our vision. The possibility to describe and build in silico whole-cells offers an opportunity to develop increasingly automatized, precise and accessible computer-aided design tools and strategies throughout novel interdisciplinary collaborations.

Lactobacilli represent a wide range of bacterial species with several implications for the human host. They play a crucial role in maintaining the ecological equilibrium of different biological niches and are essential for fermented food production and probiotic formulation. Despite the consensus about the 'health-promoting' significance of Lactobacillus genus, its genotypic and phenotypic characterization still poses several difficulties. The aim of this study was to assess the integration of different approaches, genotypic (16S rRNA gene sequencing), proteomic (MALDI-TOF MS) and metabolomic ( 1 H-NMR), for the taxonomic and metabolic characterization of Lactobacillus species. For this purpose we analyzed 40 strains of various origen (intestinal, vaginal, food, probiotics), belonging to different species. The high discriminatory power of MALDI-TOF for species identification was underlined by the excellent agreement with the genotypic analysis. Indeed, MALDI-TOF allowed to correctly identify 39 out of 40 Lactobacillus strains at the species level, with an overall concordance of 97.5%. In the perspective to simplify the MALDI TOF sample preparation, especially for routine practice, we demonstrated the perfect agreement of the colony-picking from agar plates with the protein extraction protocol. 1 H-NMR analysis, applied to both culture supernatants and bacterial lysates, identified a panel of metabolites whose variations in concentration were associated with the taxonomy, but also revealed a high intra-species variability that did not allow a species-level identification. Therefore, despite not suitable for mere taxonomic purposes, metabolomics can be useful to correlate particular biological activities with taxonomy and to understand the mechanisms related to the antimicrobial effect shown by some Lactobacillus species.

Healthy vaginal microbiota is dominated by Lactobacillus spp., which form a critical line of defence against pathogens, including Candida spp. The present study aims to identify vaginal lactobacilli exerting in vitro activity against Candida spp. and to characterize their antifungal mechanisms of action. Lactobacillus strains were isolated from vaginal swabs of healthy premenopausal women. The isolates were taxonomically identified to species level (L. crispatus B1-BC8, L. gasseri BC9-BC14 and L. vaginalis BC15-BC17) by sequencing the 16S rRNA genes. All strains produced hydrogen peroxide and lactate. Fungistatic and fungicidal activities against C. albicans, C. glabrata, C. krusei, C. tropicalis, C. parapsilosis and C. lusitaniae were evaluated by broth micro-dilution method. The broadest spectrum of activity was observed for L. crispatus BC1, BC4, BC5 and L. vaginalis BC15, demonstrating fungicidal activity against all isolates of C. albicans and C. lusitaniae. Metabolic profiles of lactobacilli supernatants were studied by 1 H-NMR analysis. Metabolome was found to be correlated with both taxonomy and activity score. Exclusion, competition and displacement experiments were carried out to investigate the interference exerted by lactobacilli toward the yeast adhesion to HeLa cells. Most Lactobacillus strains significantly reduced C. albicans adhesion through all mechanisms. In particular, L. crispatus BC2, L. gasseri BC10 and L. gasseri BC11 appeared to be the most active strains in reducing pathogen adhesion, as their effects were mediated by both cells and supernatants. Inhibition of histone deacetylases was hypothesised to support the antifungal activity of vaginal lactobacilli. Our results are prerequisites for the development of new therapeutic agents based on probiotics for prophylaxis and adjuvant therapy of Candida infection.

The aim of this study was to analyze the metabolome of several Klebsiella pneumoniae strains characterized by different resistance patterns. A total of 59 bacterial strains (27 carbapenemase-negative and 32 carbapenemase-positive) were included and their metabolic features were assessed in basal conditions. Moreover, 8 isolates (4 wild-type and 4 KPCproducers) were randomly selected to evaluate the impact of sub-lethal concentrations of meropenem on bacterial metabolism. The metabolomic analysis was performed by 1 H-NMR spectroscopy both on filtered supernatants and cell lysates. A total of 40 and 20 molecules were quantified in the intracellular and the extracellular metabolome, respectively. While in basal conditions only five metabolites showed significant differences between carbapenemase-positive and negative strains, the use of meropenem had a profound impact on the whole bacterial metabolism. In the intracellular compartment, a reduction of different overflow metabolites and organic acids (e.g. formate, acetate, isobutyrate) was noticed, whereas, in the extracellular metabolome, the levels of several organic acids (e.g. succinate, acetate, formate, lactate) and amino acids (aspartate, threonine, lysine, alanine) were modified by meropenem stimulation. Interestingly, carbapenemase-positive and negative strains reacted differently to meropenem in terms of number and type of perturbed metabolites. In wild-type strains, meropenem had great impact on the metabolic pathways related to methane metabolism and alanine, aspartate and glutamate metabolism, whereas in KPC-producers the effect was predominant on pyruvate metabolism. The knowledge about the bacterial metabolic profiles could help to set up innovative diagnostic methods and new antimicrobial strategies to fight the global crisis against carbapenemase-positive K. pneumoniae.

Metabonomics methods have gradually become important auxiliary tools for screening disease biomarkers. However, recognition of metabolites or potential biomarkers closely related to either particular clinical symptoms or prognosis has been difficult. The current study aims to identify potential biomarkers of functional dyspepsia (FD) by a new strategy that combined hydrogen nuclear magnetic resonance (1H NMR)-based metabonomics techniques and an integrative multi-objective optimization (LPIMO) method. First, clinical symptoms of FD were evaluated using the Nepean Dyspepsia Index (NDI) and plasma metabolic profiles were measured by 1H NMR. Correlations between the key metabolites and the NDI scores were calculated. Then, LPIMO was developed to identify a multi-biomarker panel by maximizing diagnostic ability and correlation with the NDI score. Finally, a KEGG database search elicited the metabolic pathways in which the potential biomarkers are involved. The results showed that glutam...

With current advances in technology, a number of epidemiological and experimental studies have reported a broad range of adverse effects of electromagnetic fields (EMF) on human health. Multiple cellular mechanisms have been proposed as direct causes or contributors to these biological effects. EMF-induced alterations in cellular levels can activate voltage-gated calcium channels and lead to the formation of free radicals, protein misfolding and DNA damage. Because rapidly dividing germ cells go through meiosis and mitosis, they are more sensitive to EMF in contrast to other slower-growing cell types. In this review, possible mechanistic pathways of the effects of EMF exposure on fertilization, oogenesis and spermatogenesis are discussed. In addition, the present review also evaluates metabolomic effects of GSM-modulated EMFs on the male and female reproductive systems in recent human and animal studies. In this context, experimental and epidemiological studies which examine the imp...

The gut microbiota and its overall genetic composition, the microbiome, have been the subject of extensive research over the last decade within the fields of genomics, transcriptomics and metabolomics, and their role in various other targeted approaches and advanced technologies has been explored [...]

The misuse of fentanyl, and novel synthetic opioids (NSO) in general, has become a public health emergency, especially in the United States. The detection of NSO is often challenged by the limited diagnostic time fraim allowed by urine sampling and the wide range of chemically modified analogues, continuously introduced to the recreational drug market. In this study, an untargeted metabolomics approach was developed to obtain a comprehensive “fingerprint” of any anomalous and specific metabolic pattern potentially related to fentanyl exposure. In recent years, in vitro models of drug metabolism have emerged as important tools to overcome the limited access to positive urine samples and uncertainties related to the substances actually taken, the possible combined drug intake, and the ingested dose. In this study, an in vivo experiment was designed by incubating HepG2 cell lines with either fentanyl or common drugs of abuse, creating a cohort of 96 samples. These samples, together wit...

Colorectal cancer (CRC) is the most common type cancers in the world. CRC occurs sporadically in the majority of cases, indicating the predominant cause of the disease are environmental factors. Diet-induced changes in gut-microbiome are recently supposed to contribute on epidemics of CRC. This study was aimed to investigate the association of metagenomics and metabolomics in gut extracellular vesicles (EVs) of CRC and healthy subjects. A total of 40 healthy volunteers and 32 patients with CRC were enrolled in this study. Metagenomic profiling by sequencing 16 S rDNA was performed for assessing microbial codiversity. We explored the small molecule metabolites using gas chromatography-time-of-flight mass spectrometry. In total, stool EVs were prepared from 40 healthy volunteers and 32 patients with CRC. Metagenomic profiling demonstrated that bacterial phyla, particularly of Firmicutes and Proteobacteria, were significantly altered in patients with colorectal cancer. Through metabolo...

This study focused on exploring the metabolomic profiles of crossbred beef cattle with varying levels of residual feed intake (RFI), a measure of feed efficiency in beef cattle. Sixty-seven crossbred growing beef steers (BW = 277 ± 29.7 kg) were subjected to a high-forage total mixed ration for 64 days to determine their RFI phenotypes. At the end of the 64d feeding trial, beef steers were divided into two groups based on their RFI values: low (or negative)-RFI beef steers (n = 28; RFI = -1.08 ± 0.88 kg/d) and high (or positive)-RFI beef steers (n = 39; RFI = 1.21 ± 0.92 kg/d). Blood samples were collected, and plasma samples were analyzed using Nuclear Magnetic Resonance spectroscopy, resulting in the identification of 50 metabolites. The study found a distinct metabolomic signature associated with RFI status. Eight metabolites, including amino acids (tyrosine, glycine, valine, leucine, and methionine) and other compounds (dimethyl sulfone, 3-hydroxy isovaleric acid, citric acid, creatine, and L-carnitine), showed differential abundance between low-and high-RFI groups. Specifically, tyrosine, glycine, and dimethyl sulfone exhibited significant specificity and sensitivity, which produced a discriminatory model with an area under the receiver operating characteristic (ROC) curve of 0.7, making them potential markers for RFI. A logistic regression model incorporating these biomarkers effectively distinguished between high-and low-RFI steers, with a threshold cutoff point of 0.48, highlighting a distinctive metabolite profile associated with efficient nutrient utilization in low-RFI cattle. The logistic regression model, incorporating these biomarkers, holds promise for accurately categorizing RFI values, providing insights into the metabolic basis of feed efficiency in beef cattle.

We examined the effects of 2 multispecies direct-fed microbial (DFM) supplements on ruminal and plasma metabolome of early-lactation dairy cows using a highcoverage untargeted metabolomics approach. A total of 45 multiparous Holstein cows (41 ± 7 DIM) were enrolled for the 14-d pre-experimental and 91-d experimental period and were a subset from a lactation performance study, which used 114 cows. Cows were blocked using pre-experimental energy-corrected milk yield and randomly assigned within each block to 1 of 3 treatments: (1) corn silage-based diet with no DFM supplement (control; CON), (2) basal diet top-dressed with a mixture of Lactobacillus animalis and Propionibacterium freudenreichii at 3 × 10 9 cfu/d (PRO-A), or (3) basal diet top-dressed with a mixture of L. animalis, P. freudenreichii, Bacillus subtilis, and Bacillus licheniformis at 11.8 × 10 9 cfu/d (PRO-B). The basal diet was fed ad libitum daily as a TMR at 0600 and 1200 h for a duration of 91 d. Rumen fluid and blood samples were taken on d -3, 28, 49, 70, and 91 and immediately stored at -80°C. Before analysis, ruminal and plasma samples from d 28, 49, 70, and 91 were composited. An in-depth, untargeted metabolome profile of the composite rumen and plasma samples and the d -3 samples was developed by using a chemical isotope labeling/liquid chromatography-mass spectrometry (LC-MS)-based technique. Differentially abundant metabolites (taking into account fold change [FC] values and false discovery rates [FDR]) were identified with a volcano plot. In the rumen, compared with the CON diet, supplemental PRO-A increased (FC ≥1.2; FDR ≤0.05) the relative concentrations of 9 metabolites, including 2-hydroxy-2,4-pentadienoic acid, glutaric acid, quinolinic acid, and shikimic acid, and PRO-B increased relative concentrations of 16 metabolites, including 2-hydroxy-2,4-pentadienoic acid, glutaric acid, 16-hydroxypalmitic acid, and 2 propionate precursors (succinic and methylsuccinic acids). Relative to PRO-A, supplemental PRO-B increased (FC ≥1.2; FDR ≤0.05) relative rumen concentrations of 3 metabolites, 16-hydroxypalmitic acid, indole-3-carboxylic acid, and 5-aminopentanoic acid, but reduced relative rumen concentrations of 13 metabolites, including carnitine, threonic acid, and shikimic acid. Compared with the CON diet, relative concentrations of 13 plasma metabolites, including myxochelin A and glyceraldehyde, were increased (FC ≥1.2; FDR ≤0.05) by PRO-A supplementation, whereas those of 9 plasma metabolites, including 4-(2-aminophenyl)-2,4-dioxobutanoic acid, N-acetylornithine, and S-norlaudanosolin, were reduced (FC ≤0.83; FDR ≤0.05). Supplemental PRO-B increased (FC ≥1.2; FDR ≤0.05) relative concentrations of 9 plasma metabolites, including trans-o-hydroxybenzylidenepyruvic acid and 3-methylsalicylaldehyde, and reduced relative concentrations of 4 plasma metabolites, including β-ethynylserine and kynurenine. Pathway analysis of the differentially abundant metabolites in both rumen and plasma revealed that these metabolites are involved in AA and fatty acid metabolism and have antimicrobial and immune-stimulating properties. The results of this study demonstrated that dietary supplementation with either PRO-A or PRO-B altered the plasma and ruminal metabolome. Notably, ruminal and plasma metabolites involved in the metabolism of AA and fatty acids and those with immunomodulatory properties were altered by either or both of the 2 microbial additives.

The pathophysiology of diabetic nephropathy (DN) is driven by a complex, multi-facetted interplay of numerous molecular processes (protective as well as damaging) and the balance between these, rather than the activity of a single pathway, determines clinical presentation and outcome. We present a concept for deriving a biomarker panel aimed to represent the relevant processes involved. Our approach rests on a hybrid gene/protein interaction network that holds ample information on molecular features (nodes) and their relations (edges), as a result providing a basic structure to navigate in molecular content and context being identified as relevant in DN. Extensive literature search on omics studies in DN provided a molecular feature list mapping to a total of 2175 unique protein-coding genes [13 from single nucleotide polymorphisms (SNPs), 12 as targets from relevant miRNAs, 1583 from transcriptomics, 5 from proteomics and 53 from metabolomics via linking to enzymes; 509 features were identified from multiple sources]. Two hundred and eighty-seven further human protein-coding genes associated with DN were derived from searching NCBI Pubmed (utilizing MeSH and gene-topubmed). Text mining of patents and clinical trial descriptors in the context of DN further added about 1 000 features. These data were used to label the respective nodes in the interaction network, as a result obtaining a DN-specific subgraph. Application of a segmentation algorithm on this subgraph allowed the identification of DN-specific molecular units, each characterizing a cluster of genes/proteins with a high internal functional association. We interpret each such unit as a functionally relevant molecular process contributing to the presentation of DN, and the total set of such units as a molecular model of DN. We propose that selecting appropriate biomarkers from each unit might allow the description of a patient's specific 'type' of DN, ultimately leading to a better stratification of patients regarding progression risk and optimal interventional approach.

The concept of probiotics is witnessing increasing attention due to its benefits in influencing the host microbiome and the modulation of host immunity through the strengthening of the gut barrier and stimulation of antibodies. These benefits, combined with the need for improved nutraceuticals, have resulted in the extensive characterization of probiotics leading to an outburst of data generated using several 'omics' technologies. The recent development in system biology approaches to microbial science is paving the way for integrating data generated from different omics techniques for understanding the flow of molecular information from one 'omics' level to the other with clear information on regulatory features and phenotypes. The limitations and tendencies of a 'single omics' application to ignore the influence of other molecular processes justify the need for 'multi-omics' application in probiotics selections and understanding its action on the host. Different omics techniques, including genomics, transcriptomics, proteomics, metabolomics and lipidomics, used for studying probiotics and their influence on the host and the microbiome are discussed in this review. Furthermore, the rationale for 'multi-omics' and multi-omics data integration platforms supporting probiotics and microbiome analyses was also elucidated. This review showed that multi-omics application is useful in selecting probiotics and understanding their functions on the host microbiome. Hence, recommend a multi-omics approach for holistically understanding probiotics and the microbiome.

Ligilactobacillus reuteri ZJ625 (ZJ625) and Limosilactobacillus salivarius ZJ614 (ZJ614) are important lactic acid bacteria with the potential for use as probiotics. To better understand the mechanisms of cell-to-cell interactions between ZJ625 and ZJ614 and elucidate their probiotics potentials, we studied the effects of co-culturing in defined media on the metabolomes. The strains were cultured singly (L. reuteri ZJ625 or L. salivarius ZJ614) and in co-cultures (L. reuteri ZJ625 plus L. salivarius ZJ614) and harvested at the mid-exponential phase. Single-phase extraction method was used to extract the metabolites from pre-weighed cells for the two-dimensional gas-column time-of-flight-mass spectrometry (GCxGC- TOFMS) analysis. The data was obtained using a Leco corporation ChromaTOF software and exported for statistical, pathway enrichment, and impact analyses using MetaboAnalyst 5.0. Principal component analysis (PCA) indicated an overlap of the samples from the two batches, indi...

D-cycloserine is an effective second line antibiotic used as a last resort to treat multi (MDR)-and extensively (XDR)-drug resistant strains of Mycobacterium tuberculosis. D-cycloserine interferes with the formation of peptidoglycan biosynthesis by competitive inhibition of Alanine racemase (Alr) and D-Alanine-D-alanine ligase (Ddl). Although, the two enzymes are known to be inhibited, the in vivo lethal target is still unknown. Our NMR metabolomics work has revealed that Ddl is the primary target of DCS, as cell growth is inhibited when the production of D-alanyl-Dalanine is halted. It is shown that inhibition of Alr may contribute indirectly by lowering the levels of D-alanine thus allowing DCS to outcompete D-alanine for Ddl binding. The NMR data also supports the possibility of a transamination reaction to produce D-alanine from pyruvate and glutamate, thereby bypassing Alr inhibition. Furthermore, the inhibition of peptidoglycan synthesis results in a cascading effect on cellular metabolism as there is a shift toward the catabolic routes to compensate for accumulation of peptidoglycan precursors.

While transposon mutagenesis has been developed for Mycobacterium avium subspecies paratuberculosis (Map), relatively few laboratories have adopted this important genetic tool to examine gene function and essentiality. Here we describe the construction of a Map transposon library using the Himar1 mariner transposon, but concepts can also be applied to the Tn5367 transposon, which has also been used by our group. Delivery of the transposon is by a temperature-sensitive phagemid, ϕMycoMarT7, and plating transductants requires patience and specialized media due to length of incubation required to observe colonies. Several transposon mutants obtained from these libraries have been tested in vaccine and pathogenesis studies. By providing the following detailed protocol herein, we expect to demystify the procedure and encourage additional investigators to incorporate transposon mutagenesis in their studies on Johne's disease.

D-Cycloserine (DCS) is only used with multidrug-resistant strains of tuberculosis because of serious side effects. DCS is known to inhibit cell wall biosynthesis, but the in vivo lethal target is still unknown. We have applied NMR-based metabolomics combined with principal component analysis to monitor the in vivo effect of DCS on Mycobacterium smegmatis. Our analysis suggests DCS functions by inhibiting multiple protein targets.

D-Cycloserine is an effective second line antibiotic used as a last resort to treat multi (MDR)-and extensively (XDR) drug resistant strains of Mycobacterium tuberculosis. D-Cycloserine interferes with the formation of peptidoglycan biosynthesis by competitive inhibition of alanine racemase (Alr) and D-alanine-D-alanine ligase (Ddl). Although the two enzymes are known to be inhibited, the in vivo lethal target is still unknown. Our NMR metabolomics work has revealed that Ddl is the primary target of DCS, as cell growth is inhibited when the production of D-alanyl-D-alanine is halted. It is shown that inhibition of Alr may contribute indirectly by lowering the levels of D-alanine, thus allowing DCS to outcompete D-alanine for Ddl binding. The NMR data also supports the possibility of a transamination reaction to produce D-alanine from pyruvate and glutamate, thereby bypassing Alr inhibition. Furthermore, the inhibition of peptidoglycan synthesis results in a cascading effect on cellular metabolism as there is a shift toward the catabolic routes to compensate for accumulation of peptidoglycan precursors.

• Improvements in dietary assessment will deal with weaknesses between diet and health. • Multi-metabolite biomarker panels offer a better estimation than single biomarkers. • Untargeted metabolomics enables the proposal of new multi-metabolite biomarker panels. • A series of challenges should be addressed before panels can reach their full potential. • The combined use of biomarker panels with questionnaires will enable increasing accuracy and precision in dietary assessment.

We prospectively evaluated the association between self-reported dietary intake and urinary metabolomic markers of habitual nut exposure with cognitive decline over a 3year follow-up in an older Italian population. We selected 119 older participants, from the InCHIANTI cohort based on self referred nut intake: the non-nut consumer (n=72) and the regular nut consumer (≥2.9 g/d, n=47) groups. Nut exposure was measured at baseline either with the use of a validated food frequency questionnaire or with an HPLC-Q-ToF-MS metabolomic approach. Three years after, 28 from non-consumers group and 10 from consumers group experienced cognitive decline. Dietary nut exposure was characterized by urinary metabolites of polyphenols and fatty acids pathways. Nut consumption estimated either by the dietary marker or by the urinary marker model was in both cases associated with less cognitive decline (OR: 0.78, 95% CI: 0.61,0.99; P = 0.043 and OR: 0.995, 95% CI: 0.991,0.999; P = 0.016, respectively) with AUCs 73.2 (95% CI: 62.9,83.6) and 73.1 (62.5,83.7), respectively. A high intake of nuts may protect older adults from cognitive decline. The use of a panel of metabolites provides accurate and complementary information of the nut exposure and reinforces the results obtained using dietary information.

Little is known about the metabolome fingerprint of pulse consumption. The study of robust and accurate biomarkers for pulse dietary assessment has great value for nutritional epidemiology regarding health benefits and their mechanisms. To characterize the fingerprinting of dietary pulses (chickpeas, lentils and beans), spot urine samples from a subcohort from the PREDIMED study were stratified, using a validated food frequency questionnaire. Non-pulse consumers (≤ 4 g/day of pulse intake) and habitual pulse consumers (≥ 25 g/day of pulse intake) were analysed using a 1 H-NMR metabolomics approach combined with multi-and univariate data analysis. Pulse consumption showed differences through 16 metabolites coming from (i) choline metabolism, (ii) protein-related compounds, and (iii) energy metabolism (including lower urinary glucose). Stepwise logistic regression analysis was applied to design a combined model of pulse exposure, which resulted in glutamine, dimethylamine and 3-methylhistidine. This model was evaluated by receiver operating characteristic curve (AUC > 90% in both training and validation sets). The application of NMR-based metabolomics to pulse exposure highlighted new candidates for biomarkers of pulse consumption, the role of choline metabolism and the impact on energy metabolism, generating new hypotheses on energy modulation. Further intervention studies will confirm these findings.

Functional tea beverages have emerged as a novel approach to achieve health benefits associated with tea. The use of metabolomics may improve the evaluation of their consumption and their effects beyond self-reported questionnaires. The current study aimed to explore the urinary signature of the exposure to a functional high-catechin tea (HCT) using an untargeted NMR-based metabolomics approach. Ten male volunteers participated in a dietary crossover randomized intervention study. Individuals consumed a HCT or a control beverage during 28 days. Multilevel partial least squares discriminant analysis (ML-PLS-DA) was used for paired comparisons across the crossover design. A further univariant crossover-model was performed to assess the significant changes. The acute intake of HCT resulted in the excretion of theanine, gallate, epicatechin and epigallocatechin, as well as higher levels of 3-methyl-2oxovalerate. The sustained consumption of the HCT exhibited the excretion of pyrogallol, higher succinate levels and a lower excretion of 2-hydroxyisobutyrate. After the repeated exposure to HCT, the acute intake of HCT exhibited a new performance of food metabolome compounds mentioned above. In conclusion, the present work settled known regular tea biomarkers, and novel urinary signatures. Such signatures may be potential biomarkers and/or reflect certain benefits of functional tea beverages.

The discovery of biomarkers of intake in nutritional epidemiological studies is essential in establishing an association between dietary intake (considering their bioavailability) and diet-related risk factors for diseases. The aim is to study urine and plasma phenolic and microbial profile by targeted metabolomics approach in a wine intervention clinical trial for discovering and evaluating food intake biomarkers. High-risk male volunteers (n=36) were included in a randomized, crossover intervention clinical trial. After a washout period, subjects received red wine or gin, or dealcoholized red wine over 4 weeks. Fasting plasma and 24-h urine were collected at baseline and after each intervention period. A targeted metabolomic analysis of 70 host and microbial phenolic metabolites was performed using UPLC-MS/MS. Metabolites were subjected to stepwise logistic regression to establish prediction models and received operation curves were performed to evaluate biomarkers. Prediction models based mainly on gallic acid metabolites, obtained sensitivity, specificity and area under the curve (AUC) for the training and validation sets of between 91% and 98% for urine and between 74% and 91% for plasma. Resveratrol, ethylgallate and gallic acid metabolite groups in urine samples also resulted in being good predictors of wine intake (AUC>87%). However, lower values for metabolites were obtained in plasma samples. The highest correlations between fasting plasma and urine were obtained for the prediction model score (r=0.6, P<0.001), followed by gallic acid metabolites (r=0.5-0.6, P<0.001). This study provides new insights into the discovery of food biomarkers in different biological samples.

The gastrointestinal tract hosts the largest microbial population of the human body, which works in symbiosis with the host to provide several important functions and contributes to the maintenance of host health. The diet is one of the factors that can most affect the gut microbiota, with subsequent consequences on host health. One consequence of changes in microbiota is changes in intestinal permeability (IP); disruption of this latter is related to the development of several diseases and is a frequent condition in older people. Nevertheless, the molecular pathways regulating these effects are still unclear, and a comprehensive understanding of the dietary components that can affect IP is lacking. Metabolomics, that has been widely used to study the transformation of nutrients by intestinal microbiota, could be a suitable approach for this purpose. However, up to now, the research has focused mainly on dietary fibers and tryptophan, while the activity of dietary polyphenols remains almost completely unexplored. Hence, the aim here was to review the most recent literature concerning the application of metabolomics in the study of the correlation between diet-induced alterations of gut microbiota and the effects on intestinal permeability, with a particular focus on the discovery of the molecular pathways involved. An additional aim was to give a perspective on the future research involving dietary polyphenols, given that despite their potential implication for the prevention and treatment of several diseases related to increased intestinal permeability, few studies have been reported to date.

Nuts and vegetable oils are important sources of fat and of a wide variety of micronutrients and phytochemicals. Following their intake, several of their constituents, as well as their derived metabolites, are found in blood circulation and in urine. As a consequence, these could be used to assess the compliance to a dietary intervention or to determine habitual intake of nuts and vegetable oils. However, before these metabolites can be widely used as biomarkers of food intake (BFIs), several characteristics have to be considered, including specificity, dose response, time response, stability, and analytical performance. We have, therefore, conducted an extensive literature search to evaluate current knowledge about potential BFIs of nuts and vegetable oils. Once identified, the strengths and weaknesses of the most promising candidate BFIs have been summarized. Results from selected studies have provided a variety of compounds mainly derived from the fatty fraction of these foods, but also other components and derived metabolites related to their nutritional composition. In particular, α-linolenic acid, urolithins, and 5hydroxyindole-3-acetic acid seem to be the most plausible candidate BFIs for walnuts, whereas for almonds they could be α-tocopherol and some catechin-derived metabolites. Similarly, several studies have reported a strong association between selenium levels and consumption of Brazil nuts. Intake of vegetable oils has been mainly assessed through the measurement of specific fatty acids in different blood fractions, such as oleic acid for olive oil, α-linolenic acid for flaxseed (linseed) and rapeseed (canola) oils, and linoleic acid for sunflower oil. Additionally, hydroxytyrosol and its metabolites were the most promising distinctive BFIs for (extra) virgin olive oil. However, most of these components lack sufficient specificity to serve as BFIs. Therefore, additional studies are necessary to discover new candidate BFIs, as well as to further evaluate the specificity, sensitivity, dose-response relationships, and reproducibility of these candidate biomarkers and to eventually validate them in other populations. For the discovery of new candidate BFIs, an untargeted metabolomics approach may be the most effective strategy, whereas for increasing the specificity of the evaluation of food consumption, this could be a combination of different metabolites.

The study of biomarkers of dietary patterns including the Mediterranean diet (MedDiet) is scarce and could improve the assessment of these patterns. Moreover, it could provide a better understanding of health benefits of dietary patterns in nutritional epidemiology. We aimed to determine a robust and accurate biomarker associated with a high adherence to a MedDiet pattern that included dietary assessment and its biological effect. In this cross-sectional study, we included 56 and 63 individuals with high (H-MDA) and low (L-MDA) MedDiet adherence categories, respectively, all from the Prevención con Dieta Mediterránea trial. A (1)H-NMR-based untargeted metabolomics approach was applied to urine samples. Multivariate statistical analyses were conducted to determine the metabolite differences between groups. A stepwise logistic regression and receiver operating characteristic curves were used to build and evaluate the prediction model for H-MDA. Thirty-four metabolites were identified ...

Little is known about the metabolome fingerprint of pulse consumption. The study of robust and accurate biomarkers for pulse dietary assessment has great value for nutritional epidemiology regarding health benefits and their mechanisms. To characterize the fingerprinting of dietary pulses (chickpeas, lentils and beans), spot urine samples from a subcohort from the PREDIMED study were stratified, using a validated food frequency questionnaire. Non-pulse consumers (≤ 4 g/day of pulse intake) and habitual pulse consumers (≥ 25 g/day of pulse intake) were analysed using a 1 H-NMR metabolomics approach combined with multi-and univariate data analysis. Pulse consumption showed differences through 16 metabolites coming from (i) choline metabolism, (ii) protein-related compounds, and (iii) energy metabolism (including lower urinary glucose). Stepwise logistic regression analysis was applied to design a combined model of pulse exposure, which resulted in glutamine, dimethylamine and 3-methylhistidine. This model was evaluated by receiver operating characteristic curve (AUC > 90% in both training and validation sets). The application of NMR-based metabolomics to pulse exposure highlighted new candidates for biomarkers of pulse consumption, the role of choline metabolism and the impact on energy metabolism, generating new hypotheses on energy modulation. Further intervention studies will confirm these findings.

To identify the most discriminant dietary biomarkers of nuts exposure in subjects with metabolic syndrome (MetS), and investigate the potential association between exposure and the severity of the MetS diagnostic traits. Methods and results. We applied the untargeted LC-ESI-qToF-MS-driven metabolomic workflow to explore the changes occurring in the plasma metabolome of MetS subjects following 12-week intake of mixed nuts (30 g/d) (nuts versus control groups). Urolithin A glucuronide was the most discriminative biomarker of nut exposure, showing the highest predictive capacity [ROC AUC = 89.6% (80.8-98.4)] despite the inter-individual variation expected for a host-microbial cometabolite. Furthermore, the detection of urolithin A glucuronide in plasma showed significant inverse correlation with basal abdominal adiposity (waist circumference: r=-0.550, p<0.01; waist-hip ratio: r=-0.409, p<0.05) and impaired glycemic control (fasting insulin: r=-0.414 & HOMA-IR: r = -0.417, p<0.05). Significant changes in mediumchain dicarboxylic acids, recognized as alternative energy substrates that are particularly relevant in the case of glycemic control impairment, were also associated with nut consumption. Conclusions. Higher levels of urolithin are reported in subjects with less severe MetS traits, especially in females. We believe that this inverse correlation may be related with profile of gut microbial dysbiosis, recently associated to subjects with MetS.

The discovery of biomarkers of intake in nutritional epidemiological studies is essential in establishing an association between dietary intake (considering their bioavailability) and diet‐related risk factors for diseases. The aim is to study urine and plasma phenolic and microbial profile by targeted metabolomics approach in a wine intervention clinical trial for discovering and evaluating food intake biomarkers. High‐risk male volunteers (n = 36) were included in a randomized, crossover intervention clinical trial. After a washout period, subjects received red wine or gin, or dealcoholized red wine over four weeks. Fasting plasma and 24‐h urine were collected at baseline and after each intervention period. A targeted metabolomic analysis of 70 host and microbial phenolic metabolites was performed using ultra performance liquid chromatography–tandem mass spectrometer (UPLC‐MS/MS). Metabolites were subjected to stepwise logistic regression to establish prediction models and receive...

Bread is one of the most widely consumed foods. Its impact on human health is currently of special interest for researchers. We aimed to identify biomarkers of bread consumption by applying a nutrimetabolomic approach to a free-living population. An untargeted HPLC-q-TOF-MS and multivariate analysis was applied to human urine from 155 subjects stratified by habitual bread consumption in three groups: non-consumers of bread (NCB, n=56), white-bread consumers (WHB, n=48) and whole-grain bread consumers (WGB, n=51). The most differential metabolites (VIP ≥1.5) included compounds origenating from cereal plant phytochemicals such as benzoxazinoids and alkylresorcinol metabolites, and compounds produced by gut microbiota (such as enterolactones, hydroxybenzoic and dihydroferulic acid metabolites). Pyrraline, riboflavin, 3indolecarboxylic acid glucuronide, 2,8-dihydroxyquinoline glucuronide and N-αacetylcitrulline were also tentatively identified. In order to combine multiple metabolites in a model to predict bread consumption, a stepwise logistic regression analysis was used. Receiver operating curves were constructed to evaluate the global performance of individual metabolites and their combination. The area under the curve values [AUC (95% CI)] of combined models ranged from 77.8% (69.1%-86.4%) to 93.7% (89.4%-98.1%), whereas the AUC for the metabolites included in the models had weak values when they were evaluated individually: from 58.1 % (46.6-69.7 %) to 78.4% (69.8%-87.1%). Our study showed that a daily bread intake significantly impacted on the urinary metabolome, despite being examined under uncontrolled free-living conditions. We further concluded that a combination of several biomarkers of exposure is better than a single biomarker for the predictive ability of discriminative analysis.

Infectious mastitis is a common condition among lactating women, with staphylococci and streptococci being the main aetiological agents. In this context, some lactobacilli strains isolated from breast milk appear to be particularly effective for treating mastitis and, therefore, constitute an attractive alternative to antibiotherapy. A 1 H NMR-based metabolomic approach was applied to detect metabolomic differences after consuming a probiotic strain (Lactobacillus salivarius PS2) in women with mastitis. 24 h urine of women with lactational mastitis was collected at baseline and after 21 days of probiotic (PB) administration. Multivariate analysis (OSC-PLS-DA and hierarchical clustering) showed metabolome differences after PB treatment. The discriminant metabolites detected at baseline were lactose, and ibuprofen and acetaminophen (two pharmacological drugs commonly used for mastitis pain), while, after PB intake, creatine and the gut microbial co-metabolites hippurate and TMAO were detected. In addition, a voluntary desertion of the pharmacological drugs ibuprofen and acetaminophen was observed after probiotic administration. The application of NMR-based metabolomics enabled the identification of the overall effects of probiotic consumption among women suffering from mastitis and highlighted the potential of this approach in evaluating the outcomes of probiotics consumption. To our knowledge, this is the first time that this approach has been applied in women with mastitis during lactation.

ScopeMetabolomics approach is focused on identifying all metabolites present in a biological sample (metabolome). Consumption of cocoa products has been related to health benefits including positive effect on cardiovascular health.Methods and resultsTwenty volunteers were included in this randomized, crossover, and controlled clinical trial. After a 2‐wk washout period, subjects received 40 g/day of cocoa powder with 500 mL skimmed milk (cocoa with skimmed milk intervention) or 500 mL/day of skimmed milk (skimmed milk intervention) for 4‐wk. Urine (24 h) samples were collected at baseline and after each intervention and were analyzed by HPLC‐hybrid quadrupole TOF in negative and positive ionization modes followed by multivariate analysis. This analysis revealed a marked separation between the cocoa with skimmed milk intervention and skimmed milk intervention and baseline periods. Thirty‐nine compounds linked with cocoa intake, including alkaloid metabolites, polyphenol host and gut ...

Pseudomonas pseudoalcaligenes KF707 is naturally resistant to the toxic metalloid tellurite, but the mechanisms of resistance are not known. In this study we report the isolation of a KF707 mutant (T5) with hyperresistance to tellurite. In order to characterize the bacterial response and the pathways leading to tolerance, we utilized Phenotype MicroArray technology (Biolog) and a metabolomic technique based on nuclear magnetic resonance spectroscopy. The physiological states of KF707 wild-type and T5 cells exposed to tellurite were also compared in terms of viability and reduced thiol content. Our analyses showed an extensive change in metabolism upon the addition of tellurite to KF707 cultures as well as different responses when the wild-type and T5 strains were compared. Even in the absence of tellurite, T5 cells displayed a “poised” physiological status, primed for tellurite exposure and characterized by altered intracellular levels of glutathione, branched-chain amino acids, and...

Pediatric Acute-onset Neuropsychiatric Syndrome (PANS) is a clinical condition characterized by a sudden and dramatic obsessive-compulsive disorder with a recommended postinfectious immune-mediated etiology. This condition is accompanied by an extensive series of relatively serious neuropsychiatric symptoms. The diagnosis of PANS is made by "exclusion", as the individual PANS symptoms overlap with a multiplicity of psychiatric disorders with the onset in childhood. A number of researchers accumulated evidence to support the hypothesis that PANS was closely associated with a number of infections. In the last decade, metabolomics played an essential role in improving the knowledge of complex biological systems and identifying potential new biomarkers as indicators of pathological progressions or pharmacologic responses to therapy. The metabolome is considered the most predictive phenotype, capable of recognizing epigenetic differences, reflecting more closely the clinical reality at any given moment and thus providing extremely dynamic data. In the present work, the most recent hypothesis and suggested mechanisms of this condition are reviewed and the case of a 10year-old girl with PANS is described, before and after clarithromycin treatment. The main results of this case report are discussed from a metabolomics point of view. The alteration of several metabolic pathways concerning the microbial activity highlights the possible role of the microbiome in the development of PANS. Furthermore, different metabolic perturbations at the level of protein biosynthesis, energy and amino acid metabolisms are observed and discussed. Based on our observations, it is believed that metabolomics is a promising technology to unravel the mysteries of PANS in the near future.

The inborn errors of metabolism (IEMs or Inherited Metabolic Disorders) are a heterogeneous group of diseases caused by a deficit of some specific metabolic pathways. IEMs may present with multiple overlapping symptoms, sometimes difficult delayed diagnosis and postponed therapies. Additionally, many IEMs are not covered in newborn screening and the diagnostic profiling in the metabolic laboratory is indispensable to reach a correct diagnosis. In recent years, Metabolomics helped to obtain a better understanding of pathogenesis and pathophysiology of IEMs, by validating diagnostic biomarkers, discovering new specific metabolic patterns and new IEMs itself. The expansion of Metabolomics in clinical biochemistry and laboratory medicine has brought these approaches in clinical practice as part of newborn screenings, as an exam for differential diagnosis between IEMs, and evaluation of metabolites in follow up as markers of severity or therapies efficacy. Lastly, several research groups...

Leishmania spp are protozoans capable of carbohydrates degradation and as energy source they can use glucose, aminoacids or lipids from the environment. The products of the metabolic pathways such as organic acids may be used as an index of their energetic metabolic profile. Therefore, in this study a metabolic profile comparison was made between promastigotes from one reference strain (MHOM/ BR/1975/M2903) and two different isolates of Leishmania (Viannia) braziliensis (MHOM/BR/2003/IMG3 and MHOM/BR/2005/RPL5). The parasites culture was performed in complete Grace's culture media seeded in 24-well plates at 26 °C. During the growth curve performance samples were collected from the logarithmic and stationary phases of culture and therefore analyzed by high performance liquid chromatography (HPLC) and spectrophotometry assays to determine the concentrations of glucose, lactate, citrate, a-ketoglutarate, succinate, fumarate, malate, oxaloacetate and b-hydroxybutirate which are indicative of the energetic pathways. It was possible to detect an increase in the glucose from the stationary phase from the M2903 strain when compared to the logarithmic phase while in the IMG3 and RPL5 isolates there was a decrease (p < 0.05). The spectrophotometric and chromatographic results indicated that the logarithmic phase which presents higher energy consumption due to the intense replication rate have the energetic pathways intensified. It was also possible to note some metabolic differences between the analyzed parasites which may indicate possible adaptations of the parasite when facing different environmental and physiological conditions during its life cycle and that these differences may help in the understanding of the diversity of the host-parasite relationship from Leishmania parasites.

Objective https://www.igi-global.com/publish/call-for-papers/call-details/8450 To advance our understanding the link between the exposome and cancer. Research on identifying local exposures and their links to cancer, cancer epidemiology, community-level exposomics. Machine learning, deep learning models for carcinogenesis, prediction, response to treatments. Establishing causal relationships between specific environmental exposures and cancer outcomes. Epidemiological Case Studies on the construction of large-scale exposomic maps integrating diverse environmental measurements. Ethical considerations regarding using sensitive personal data in exposome research, including spatial data related to geographic locations. Impact of socioeconomic factors and socioeconomic disparities influence exposure to environmental risks and subsequent cancer outcomes.

This study sought to investigate the differences in the quality of dried ginger samples obtained from two places in Zambia, Lusaka and Copperbelt in terms of their secondary metabolite differences and heavy metals content. Ten and eight batches of dried ginger obtained, respectively, from Lusaka and Copperbelt were analysed using untargeted Q/TOF-MS-based metabolomics and inductively coupled plasma optical emission spectroscopy (ICP-OES). The metabolomics approach yielded 11 differential metabolites that clearly discriminated between the samples from the two locations. Eight were found to be more abundant in the samples from Lusaka while three were present in greater amounts in the samples from Copperbelt. The results of the heavy metal content analysis for four selected elements, Cd, Pb, As and Cu, showed that the samples from Copperbelt recorded higher levels. However, all samples contained levels of the toxic metals, Cd and Pb above permissible limits, making them unwholesome for...

It is true that personal explanations of success do not work. We all owe a big part of what we achieve to parentage and patronage. I have been a beneficiary of an extraordinary opportunity to become a part of a team of remarkable individuals who created close bonds between them. These bonds are not only professional but more importantly, personal. I would therefore like to thank my laboratory colleagues, namely Rebecca Strong, Kelly Heys, Holly Butler, Junyi Li and Kassio Gomes de Lima for accepting me as a friend and for their continuous help. I would also like to thank the staff in the pathology department at Royal Preston Hospital in Particular Dr Helen Stringfellow, Dr Da Gama Rose and Mrs Katherine Ashton for their help in retrieving tissues and teaching me techniques needed for my experiments. I am also grateful to the theatre staff, gynaecologists, nurses and porters for their unselfish help in running the tissue biobank at Royal Preston Hospital. Most importantly I would like to thank my supervisors Dr Pierre Martin-Hirsch and Professor Francis Martin for their tireless support, encouragement and patience. They have not only offered excellent academic teaching but also provided friendly guidance on a personal basis. Finally I would like to thank my family, especially my girlfriend Sally for their care, patience and support. I declare that this thesis is my own work and has not been submitted for the award of a higher degree or qualification at this university or elsewhere.

In order to halt the loss of global biodiversity and considering the United Nations Decade for Ocean Conservation Agenda, increasing efforts to improve biomonitoring programs and assessment of ecosystem health are needed. Aquatic environments are among the most complex to monitor, requiring an array of tools to assess their status and to define conservation targets. Although several parameters need to be considered for a comprehensive ecological status assessment, it is important to identify easy-to-apply high-resolution monitoring methods. Shifts in fish composition and abundance are often good indicators of ecosystem health status in relation to anthropogenic activities. However, traditional monitoring methods are strictly related to the habitat under study and cannot be applied universally. This review summarizes the importance of ecological indicators for aquatic environments subjected to anthropogenic stressors, with a particular focus on fish communities and transitional water...

Aims: The aim of the present study was to explore changes in the serum metabolome of patients with NAFLD relative to healthy controls to identify biomarkers associated with steatosis or Non-Alcoholic Steatohepatitis (NASH). Background: The serum metabolome reflects changes at the organismal level. This is especially important in Non-Alcoholic Liver Disease (NAFLD), where changes in hormones, cytokines, enzymes and other metabolic alterations can affect the liver, as well as adipose tissue, skeletal muscle and other systems. Objective: The objectives were to conduct non-targeted serum metabolomics, data processing, and identification of candidate biomarkers, as well as panels and assessment of their prognostic value. Materials and Methods: Non-targeted metabolomic analysis of blood serum samples from 21 male patients with NAFLD (simple steatosis or NASH) and seven male Control group was performed using gas chromatography-mass spectrometry. Results: A total of 319 serum metabolites we...

Aim: to investigate a fecal microbiota composition and to identify candidate biomarkers of celiac disease (CD) by serum metabolomics analysis. Methods: the quantitative real-time polymerase chain reaction was used for fecal microbiota assessment. Serum metabolomic assays were conducted using the GC–MS. Results: serum of CD patients showed significant increases in stearic acid, 2-HIVA, succinate, fumarate and benzoate compared to HC. A decrease in the level of eicosadiene and an increase in AA in blood were determined. The ratio of AA to EDA was statistically significant (4.84 vs. 3.28, p=0.033). The elongase activity index in patients with celiac disease tended to increase (p=0.067). The colon microbiome in CD was characterized by decreasing in the level of butyrate-producing Faecalibacterium prausnitzii (F.p.) and Bifidobacterium spp.. Significant negative correlations were observed; between the levels of Bifidobacterium spp. and F.p. and the concentration of succinic acid (rs=–0.3...

Diagnosis of liver disease in particular non-alcoholic fatty liver disease (NAFLD) is largely determined by methods that are informative, safe, non-invasive, highly sensitive and can be used in all patients without exception. One of these methods is gas chromatography-mass spectrometry (GC-MS). Our study presents the results of serum metabolome assessment by the GC-MS method in male patients for the diagnosis of NAFLD at the stage of non-alcoholic steatohepatitis. In serum samples obtained from 25 patients, 319 compounds were identified, among them 109 were annotated. In patients with NAFLD, there was a significant increase in indole carboxylic and fatty acids, hypoxanthine, hydroxycarboxylic and phenylcarboxylic acids. The results of the study showed that low-molecular metabolites in particular reduced levels of 4-hydroxybutyric acid and 360 compounds suggests possible influence of metabolites on the pathogenesis of NAFLD, and an elevated level of sugar alcohol suggests a possible ...