Innovative Biomarkers for Obesity and Type 1 Diabetes Based on Bifidobacterium and Metabolomic Profiling.

The role of Bifidobacterium species and microbial metabolites such as short-chain fatty acids (SCFAs) and human milk oligosaccharides in controlling intestinal inflammation and the pathogenesis of obesity and type 1 diabetes (T1D) has been largely studied in recent years. This paper discusses the discovery of signature biomarkers for obesity and T1D based on data from a novel test for profiling several Bifidobacterium species, combined with metabolomic analysis. Through the NUTRISHIELD clinical study, a total of 98 children were recruited: 40 healthy controls, 40 type 1 diabetics, and 18 obese children. Bifidobacterium profiles were assessed in stool samples through an innovative test allowing high taxonomic resolution and precise quantification, while SCFAs and branched amino acids were measured in urine samples through gas chromatography-mass spectrometry (GC-MS). KIDMED questionnaires were used to evaluate the children's dietary habits and correlate them with the Bifidobacterium and metabolomic profiles. We found that B. longum subs. infantis and B. breve were higher in individuals with obesity, while B. bifidum and B. longum subs. longum were lower compared to healthy individuals. In individuals with T1D, alterations were found at the metabolic level, with an overall increase in the level of the most measured metabolites. The high taxonomic resolution of the Bifidobacterium test used meant strong correlations between the concentrations of valine and isoleucine, and the relative abundance of some Bifidobacterium species such as B. longum subs. infantis, B. breve, and B. bifidum could be observed.

AFM-IR for Nanoscale Chemical Characterization in Life Sciences: Recent Developments and Future Directions.

Despite the ubiquitous absorption of mid-infrared (IR) radiation by virtually all molecules that belong to the major biomolecules groups (proteins, lipids, carbohydrates, nucleic acids), the application of conventional IR microscopy to the life sciences remained somewhat limited, due to the restrictions on spatial resolution imposed by the diffraction limit (in the order of several micrometers). This issue is addressed by AFM-IR, a scanning probe-based technique that allows for chemical analysis at the nanoscale with resolutions down to 10 nm and thus has the potential to contribute to the investigation of nano and microscale biological processes. In this perspective, in addition to a concise description of the working principles and operating modes of AFM-IR, we present and evaluate the latest key applications of AFM-IR to the life sciences, summarizing what the technique has to offer to this field. Furthermore, we discuss the most relevant current limitations and point out potential future developments and areas for further application for fruitful interdisciplinary collaboration.

Fast profiling of primary, secondary, conjugated, and sulfated bile acids in human urine and murine feces samples.

Bile acids (BAs) are a complex class of metabolites that have been described as specific biomarkers of gut microbiota activity. The development of analytical methods allowing the quantification of an ample spectrum of BAs in different biological matrices is needed to enable a wider implementation of BAs as complementary measures in studies investigating the functional role of the gut microbiota. This work presents results from the validation of a targeted ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method for the determination of 28 BAs and six sulfated BAs, covering primary, secondary, and conjugated BAs. The analysis of 73 urine and 20 feces samples was used to test the applicability of the method. Concentrations of BAs in human urine and murine feces were reported, ranging from 0.5 to 50 nmol/g creatinine and from 0.012 to 332 nmol/g, respectively. Seventy-nine percent of BAs present in human urine samples corresponded to secondary conjugated BAs, while 69% of BAs present in murine feces corresponded to primary conjugated BAs. Glycocholic acid sulfate (GCA-S) was the most abundant BA in human urine samples, while taurolithocholic acid was the lowest concentrated compound detected. In murine feces, the most abundant BAs were α-murocholic, deoxycholic, dehydrocholic, and ß-murocholic acids, while GCA-S was the lowest concentrated BA. The presented method is a non-invasive approach for the simultaneous assessment of BAs and sulfated BAs in urine and feces samples, and the results will serve as a knowledge base for future translational studies focusing on the role of the microbiota in health.

Fact-based nutrition for infants and lactating mothers-The NUTRISHIELD study.

Background: Human milk (HM) is the ideal source of nutrients for infants. Its composition is highly variable according to the infant's needs. When not enough own mother's milk (OMM) is available, the administration of pasteurized donor human milk (DHM) is considered a suitable alternative for preterm infants. This study protocol describes the NUTRISHIELD clinical study. The main objective of this study is to compare the % weight gain/month in preterm and term infants exclusively receiving either OMM or DHM. Other secondary aims comprise the evaluation of the influence of diet, lifestyle habits, psychological stress, and pasteurization on the milk composition, and how it modulates infant's growth, health, and development. Methods and design: NUTRISHIELD is a prospective mother-infant birth cohort in the Spanish-Mediterranean area including three groups: preterm infants <32 weeks of gestation (i) exclusively receiving (i.e., >80% of total intake) OMM, and (ii) exclusively receiving DHM, and (iii) term infants exclusively receiving OMM, as well as their mothers. Biological samples and nutritional, clinical, and anthropometric characteristics are collected at six time points covering the period from birth and until six months of infant's age. The genotype, metabolome, and microbiota as well as the HM composition are characterized. Portable sensor prototypes for the analysis of HM and urine are benchmarked. Additionally, maternal psychosocial status is measured at the beginning of the study and at month six. Mother-infant postpartum bonding and parental stress are also examined. At six months, infant neurodevelopment scales are applied. Mother's concerns and attitudes to breastfeeding are registered through a specific questionnaire. Discussion: NUTRISHIELD provides an in-depth longitudinal study of the mother-infant-microbiota triad combining multiple biological matrices, newly developed analytical methods, and ad-hoc designed sensor prototypes with a wide range of clinical outcome measures. Data obtained from this study will be used to train a machine-learning algorithm for providing dietary advice to lactating mothers and will be implemented in a user-friendly platform based on a combination of user-provided information and biomarker analysis. A better understanding of the factors affecting milk's composition, together with the health implications for infants plays an important role in developing improved strategies of nutraceutical management in infant care. Clinical trial registration: https://register.clinicaltrials.gov, identifier: NCT05646940.

Joint Microbiota Activity and Dietary Assessment through Urinary Biomarkers by LC-MS/MS.

Accurate dietary assessment in nutritional research is a huge challenge, but essential. Due to the subjective nature of self-reporting methods, the development of analytical methods for food intake and microbiota biomarkers determination is needed. This work presents an ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS) method for the quantification and semi quantification of 20 and 201 food intake biomarkers (BFIs), respectively, as well as 7 microbiota biomarkers applied to 208 urine samples from lactating mothers (M) (N = 59). Dietary intake was assessed through a 24 h dietary recall (R24h). BFI analysis identified three distinct clusters among samples: samples from clusters 1 and 3 presented higher concentrations of most biomarkers than those from cluster 2, with dairy products and milk biomarkers being more concentrated in cluster 1, and seeds, garlic and onion in cluster 3. Significant correlations were observed between three BFIs (fruits, meat, and fish) and R24h data (r > 0.2, p-values < 0.01, Spearman correlation). Microbiota activity biomarkers were simultaneously evaluated and the subgroup patterns detected were compared to clusters from dietary assessment. These results evidence the feasibility, usefulness, and complementary nature of the determination of BFIs, R24h, and microbiota activity biomarkers in observational nutrition cohort studies.

Isolation and Lipidomic Screening of Human Milk Extracellular Vesicles.

Extracellular vesicles (EVs) are secreted by cells and can be found in biological fluids (e.g., blood, saliva, urine, cerebrospinal fluid, and milk). EV isolation needs to be optimized carefully depending on the type of biofluid and tissue. Human milk (HM) is known to be a rich source of EVs, and they are thought to be partially responsible for the benefits associated with breastfeeding. Here, a workflow for the isolation and lipidomic analysis of HM-EVs is described. The procedure encompasses initial steps such as sample collection and storage, a detailed description for HM-EV isolation by multistage ultracentrifugation, metabolite extraction, and analysis by liquid chromatography coupled to mass spectrometry, as well as data analysis and curation.

Solvent-Free Lipid Separation and Attenuated Total Reflectance Infrared Spectroscopy for Fast and Green Fatty Acid Profiling of Human Milk.

This study presents the first mid-infrared (IR)-based method capable of simultaneously predicting concentrations of individual fatty acids (FAs) and relevant sum parameters in human milk (HM). Representative fat fractions of 50 HM samples were obtained by rapid, two-step centrifugation and subsequently measured with attenuated total reflection IR spectroscopy. Partial least squares models were compiled for the acquired IR spectra with gas chromatography-mass spectrometry (GC-MS) reference data. External validation showed good results particularly for the most important FA sum parameters and the following individual FAs: C12:0 (R2P = 0.96), C16:0 (R2P = 0.88), C18:1cis (R2P = 0.92), and C18:2cis (R2P = 0.92). Based on the obtained results, the effect of different clinical parameters on the HM FA profile was investigated, indicating a change of certain sum parameters over the course of lactation. Finally, assessment of the method's greenness revealed clear superiority compared to GC-MS methods. The reported method thus represents a high-throughput, green alternative to resource-intensive established techniques.

GC-MS analysis of short chain fatty acids and branched chain amino acids in urine and faeces samples from newborns and lactating mothers.

BACKGROUND: Short chain fatty acids (SCFAs) and branched chain amino acids (BCAAs) are frequently determined in faeces, and widely used as biomarkers of gut-microbiota activity. However, collection of faeces samples from neonates is not straightforward, and to date levels of these metabolites in newborn's faeces and urine samples have not been described. METHODS: A targeted gas chromatography - mass spectrometry (GC-MS) method for the determination of SCFAs and BCAAs in both faeces and urine samples has been validated. The analysis of 210 urine and 137 faeces samples collected from preterm (PI), term infants (TI) and their mothers was used to report faecal and urinary SCFA and BCAA levels in adult and neonatal populations. RESULTS: A significant correlation among five SCFAs and BCAAs in faeces and urine samples was observed. Reference ranges of SCFAs and BCAAs in mothers, PI and TI were reported showing infant's lower concentrations in faeces and higher concentrations in urine. CONCLUSION: This method presents a non-invasive approach for the simultaneous assessment of SCFAs and BCAAs in faecal and urine samples and the results will serve as a knowledge base for future experiments that will focus on the study of the impact of nutrition on the microbiome of lactating mothers and their infants.

The effect of Holder pasteurization on the lipid and metabolite composition of human milk.

Human milk (HM) is the gold standard for newborn nutrition. When own mother's milk is not sufficiently available, pasteurized donor human milk becomes a valuable alternative. In this study we analyzed the impact of Holder pasteurization (HoP) on the metabolic and lipidomic composition of HM. Metabolomic and lipidomic profiles of twelve paired HM samples were analysed before and after HoP by liquid chromatography-mass spectrometry (MS) and gas chromatography-MS. Lipidomic analysis enabled the annotation of 786 features in HM out of which 289 were significantly altered upon pasteurization. Fatty acid analysis showed a significant decrease of 22 out of 29 detectable fatty acids. The observed changes were associated to five metabolic pathways. Lipid ontology enrichment analysis provided insight into the effect of pasteurization on physical and chemical properties, cellular components, and functions. Future research should focus on nutritional and/or developmental consequences of these changes.

Fatty Acid Determination in Human Milk Using Attenuated Total Reflection Infrared Spectroscopy and Solvent-Free Lipid Separation.

This study introduces the first mid-infrared (IR)-based method for determining the fatty acid composition of human milk. A representative milk lipid fraction was obtained by applying a rapid and solvent-free two-step centrifugation method. Attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy was applied to record absorbance spectra of pure milk fat. The obtained spectra were compared to whole human milk transmission spectra, revealing the significantly higher degree of fatty acid-related spectral features in ATR FT-IR spectra. Partial least squares (PLS)-based multivariate regression equations were established by relating ATR FT-IR spectra to fatty acid reference concentrations, obtained with gas chromatography-mass spectrometry (GC-MS). Good predictions were achieved for the most important fatty acid sum parameters: saturated fatty acids (SAT, R2CV = 0.94), monounsaturated fatty acids (MONO, R2CV = 0.85), polyunsaturated fatty acids (PUFA, R2CV = 0.87), unsaturated fatty acids (UNSAT, R2CV = 0.91), short-chain fatty acids (SCFA, R2CV = 0.79), medium-chain fatty acids (MCFA, R2CV = 0.97), and long-chain fatty acids (LCFA, R2CV = 0.88). The PLS selectivity ratio (SR) was calculated in order to optimize and verify each individual calibration model. All mid-IR regions with high SR could be assigned to absorbances from fatty acids, indicating high validity of the obtained models.

Oxidative stress biomarkers in the preterm infant.

Oxidative stress (OS) plays a key role in the pathophysiology of preterm infants. Accurate assessment of OS remains an analytical challenge that has been partially addressed during the last few decades. A plethora of approaches have been developed to assess preterm biofluids to demonstrate a link postnatally with preterm OS, giving rise to a set of widely employed biomarkers. However, the vast number of different analytic methods and lack of standardization hampers reliable comparison of OS-related biomarkers. In this chapter, we discuss approaches for the study of OS in prematurity with respect to methodologic considerations, the metabolic source of different biomarkers and their role in clinical studies.

Current Practice in Untargeted Human Milk Metabolomics.

Human milk (HM) is considered the gold standard for infant nutrition. HM contains macro- and micronutrients, as well as a range of bioactive compounds (hormones, growth factors, cell debris, etc.). The analysis of the complex and dynamic composition of HM has been a permanent challenge for researchers. The use of novel, cutting-edge techniques involving different metabolomics platforms has permitted to expand knowledge on the variable composition of HM. This review aims to present the state-of-the-art in untargeted metabolomic studies of HM, with emphasis on sampling, extraction and analysis steps. Workflows available from the literature have been critically revised and compared, including a comprehensive assessment of the achievable metabolome coverage. Based on the scientific evidence available, recommendations for future untargeted HM metabolomics studies are included.