1. Investigación

Background: The pathological mechanism of the gastrointestinal forms of food aller-gies is less understood in comparison to other clinical phenotypes, such as asthmaand anaphylaxis Importantly, high-IgE levels are a poor prognostic factor in gastroin-testinal allergies.Methods: This study investigated how high-IgE levels influence the development ofintestinal inflammation and the metabolome in allergic enteritis (AE), using IgE knock-in (IgEki) mice expressing high levels of IgE. In addition, correlation of the altered me-tabolome with gut microbiome was analysed.Results: Ovalbumin-sensitized and egg-white diet-fed (OVA/EW) BALB/c WT micedeveloped moderate AE, whereas OVA/EW IgEki mice induced more aggravated in-testinal inflammation with enhanced eosinophil accumulation. Untargeted metabo-lomics detected the increased levels of N-tau-methylhistamine and 2,3-butanediol,and reduced levels of butyric acid in faeces and/or sera of OVA/EW IgEki mice, whichwas accompanied with reduced Clostridium and increased Lactobacillus at the genus level. Non-sensitized and egg-white diet-fed (NC/EW) WT mice did not exhibit anysigns of AE, whereas NC/EW IgEki mice developed marginal degrees of AE. Comparedto NC/EW WT mice, enhanced levels of lysophospholipids, sphinganine and sphin-gosine were detected in serum and faecal samples of NC/EW IgEki mice. In addi-tion, several associations of altered metabolome with gut microbiome—for exampleAkkermansia with lysophosphatidylserine—were detected.Conclusions: Our results suggest that high-IgE levels alter intestinal and systemic levelsof endogenous and microbiota-associated metabolites in experimental AE. This studycontributes to deepening the knowledge of molecular mechanisms for the developmentof AE and provides clues to advance diagnostic and therapeutic strategies of allergicdiseases

Background: The selection of the sample treatment strategy is a crucial step in the metabolomics workflow. Solid phase microextraction (SPME) is a sample processing methodology with great potential for use in untargeted metabolomics of tissue samples. However, its utilization is not as widespread as other standard protocols involving steps of tissue collection, metabolism quenching, homogenization, and extraction of metabolites by solvents. Since SPME allows us to perform all these steps in one action in tissue samples, in addition to other advantages, it is necessary to know whether this methodology produces similar or comparable metabolome and lipidome coverage and performance to classical methods. Results: SPME and homogenization with solid-liquid extraction (Homo-SLE) sample treatment methods were applied to healthy murine kidney tissue, followed by comprehensive metabolomics and lipidomics analyses. In addition, it has been tested whether freezing and storage of the tissue causes alterations in the renal metabolome and lipidome, so the analyses were performed on fresh and frozen tissue samples Lipidomics analysis revealed the exclusive presence of different structural membrane and intracellular lipids in the Homo-SLE group. Conversely, all annotated metabolites were detected in both groups. Notably, the freezing of the sample mainly causes a decrease in the levels of most lipid species and an increase in metabolites such as amino acids, purines, and pyrimidines. These alterations are principally detected in a statistically significant way by SPME methodology. Finally, the samples of both methodologies show a positive correlation in all the analyses. Significance: These results demonstrate that in SPME processing, as long as the fundamentals of non-exhaustive extraction in a pre-equilibrium kinetic regime, extraction in a tissue localized area, the chemistry of the fiber coating and non-homogenization of the tissue are taken into account, is an excellent method to use in kidney tissue metabolomics; since this methodology presents an easy-to-use, efficient, and less invasive approach that simplifies the different sample processing steps.

The human gut microbiome establishes and matures during infancy, and dysregulation at this stage may lead to pathologies later in life. We conducted a multi-omics study comprising three generations of family members to investigate the early development of the gut microbiota. Fecal samples from 200 individuals, including infants (0-12 months old; 55% females, 45% males) and their respective mothers and grandmothers, were analyzed using two independent metabolomics platforms and metagenomics. For metabolomics, gas chromatography and capillary electrophoresis coupled to mass spectrometry were applied. For metagenomics, both 16S rRNA gene and shotgun sequencing were performed. Here we show that infants greatly vary from their elders in fecal microbiota populations, function, and metabolome. Infants have a less diverse microbiota than adults and present differences in several metabolite classes, such as short- and branched-chain fatty acids, which are associated with shifts in bacterial populations. These findings provide innovative biochemical insights into the shaping of the gut microbiome within the same generational line that could be beneficial in improving childhood health outcomes.

Allergic asthma is a prominent disease especially during childhood. Indoor allergens, in general, and particularly house dust mites (HDM) are the most prevalent sensitizers associated with allergic asthma. Available data show that 65–130 million people are mite-sensitized world-wide and as many as 50% of these are asthmatic. In fact, sensitization to HDM in the first years of life can produce devastating effects on pulmonary function leading to asthmatic syndromes that can be fatal. To date, there has been considerable research into the pathological pathways and structural changes associated with allergic asthma. However, limitations related to the disease heterogeneity and a lack of knowledge into its pathophysiology have impeded the generation of valuable data needed to appropriately phenotype patients and, subsequently, treat this disease. Here, we report a systematic and integral analysis of the disease, from airway remodelling to the immune response taking place throughout the disease stages. We present an overview of metabolomics, the management of complex multifactorial diseases through the analysis of all possible metabolites in a biological sample, obtaining a global interpretation of biological systems. Special interest is placed on the challenges to obtain biological samples and the methodological aspects to acquire relevant information, focusing on the identification of novel biomarkers associated with specific phenotypes of allergic asthma. We also present an overview of the metabolites cited in the literature, which have been related to inflammation and immune response in asthma and other allergy-related diseases.

Short-chain fatty acids (SCFAs) are organic saturated monocarboxylic acids with fewer than six carbon atoms. Their recently described relevance in health and disease has brought to the table the need for a convenient method for their analysis. The current research presents an optimized and validated LC-QqQ-MS method for the absolute quantification of SCFAs in plasma and feces. This method has proven to be accurate and precise in a wide range of concentrations (0.2 – 200 µM). It has been applied to more than 500 samples showing good precision, reproducibility, and linearity results. The method was applied to study samples from anorexia nervosa (AN) patients and matched healthy controls (HC). The results showed significant differences in the concentration of plasmatic and fecal SCFAs between both groups whose implications in AN are yet to be determined. Nonetheless, these findings denote important alterations in the SCFAs homeostasis in AN which can be linked to the metabolic alterations and the intestinal dysbiosis already characterized in the disease. More research is still required to identify the function of these metabolites in the pathophysiology of AN, but the present work provides a reliable methodology and valuable information to continue delving into the potential role of the microbiota as a therapeutic target via the gut-brain axis.

Metabolomics has become an essential discipline in the study of microbiome, emerging gas chromatography coupled to mass spectrometry as the most mature, robust, and reproducible analytical technique. Silylation is the most widely used chemical derivatization strategy, although it has some limitations. In this regard, alkylation by alkyl chloroformate offers some advantages, such as a rapid reaction, milder conditions, better reproducibility, and the generation of more stable derivatives. However, commercial spectral libraries do not include many of the alkyl derivatives, mainly for polyfunctional metabolites, which can form multiple derivatives. That introduces a huge bias in untargeted metabolomics leading to common errors such as duplicates, unknowns, misidentifications, wrong assignations, and incomplete results from which non-reliable findings and conclusions will be retrieved. For this reason, the purpose of this study is to overcome these shortcomings and to expand the knowledge of metabolites in general and especially those closely related to the gut microbiota through the thorough study of the reactivity of the different functional groups in real matrix derivatized by methyl chloroformate, a common representative alkylation reagent. To this end, a systematic workflow has been developed based on exhaustive structural elucidation, along with computational simulation, and taking advantage of the high sensitivity and high-resolution gas chromatography-mass spectrometry. Several empirical rules have been established according to chemically different entities (free fatty acids, amino acids, polyols, sugars, amines, and polyfunctional groups, etc.) to predict the number of derivatives formed from a single metabolite, as well as their elution order and structure. In this work, some methyl chloroformate derivatives not previously reported as well as the mechanisms to explain them are given. Extremely important is the interconversion of E- and Z- geometric isomers of unsaturated dicarboxylic acids (case of fumaric-maleic and case of citraconic-mesaconic acids), or the formation of cycled derivatives for amino acids, as well as common metabolites, as in the case of serine and cysteine, and many others.

Oxylipins are bioactive lipid mediators that participate in a wide range of processes, from blood flow to inflammation. In recent years, their exhaustive characterization as potential biomarkers has been actively pursued. However, several analytical challenges and sources of variability, like the low abundance of oxylipins in samples, their structural diversity, and the lack of harmonized and validated protocols for sample selection, collection, storage, and preparation have hampered their translation into clinical settings. In this review, these sources of variability are addressed and are exemplified with their application in recent clinical studies in different diseases. Our overall analysis highlights the need to achieve harmonized protocols for generating reliable and reproducible results that could be integrated into clinical practice to reach their full diagnostic and prognostic potential.

Urine analysis has remained a fundamental and widely used method in clinical diagnostics for over a century. With its minimal invasive nature and comprehensive range of analytes, urine has established itself as a clinical diagnostic tool for various disorders, including renal, urological, metabolic, and endocrine diseases. Furthermore, urine’s unique attributes make it an attractive matrix for biomarker discovery, as well as in assessing the metabolic and physiological states of patients and healthy individuals alike. However, limitations in our knowledge of average values and sources of urinary lipids decrease the wider clinical application of urinary lipidomics. In this context, untargeted lipidomics analysis relies heavily on the extraction and analysis of lipids in biological samples. Nevertheless, this type of analysis presents challenges in lipid identification due to the diverse nature of lipids. Therefore, proper sample treatment before analysis is crucial to obtain robust and reproducible lipidomic profiles. To address this gap, we conducted a comparative study of a urine pool sample collected from twenty healthy volunteers using four different lipid extraction methods: one biphasic and three monophasic protocols. The extracted lipids were then analyzed using UHPLC-MS and MS/MS, and the semi-quantification of all the accurately annotated lipid species was performed for each extraction method.

GC-MS for untargeted metabolomics is a well-established technique. Small molecules and molecules made volatile by derivatization can be measured and those compounds are key players in main biological pathways. This tutorial provides ready-to-use protocols for GC-MS-based metabolomics, using either the well-known low-resolution approach (GC-Q-MS) with nominal mass or the more recent high-resolution approach (GC-QTOF-MS) with accurate mass, discussing their corresponding strengths and limitations. Analytical procedures are covered for different types of biofluids (plasma/serum, bronchoalveolar lavage, urine, amniotic fluid) tissue samples (brain/hippocampus, optic nerve, lung, kidney, liver, pancreas) and samples obtained from cell cultures (adipocytes, macrophages, Leishmania promastigotes, mitochondria, culture media). Together with the sample preparation and data acquisition, data processing strategies are described specially focused on Agilent equipments, including deconvolution software and database annotation using spectral libraries. Manual curation strategies and quality control are also deemed. Finally, considerations to obtain a semiquantitative value for the metabolites are also described. As a case study, an illustrative example from one of our experiments at CEMBIO Research Centre, is described and findings discussed.

Plasmid-mediated antimicrobial resistance is one of the major threats to public health worldwide. The mechanisms involved in the plasmid/host coadaptation are still poorly characterized, and their understanding is crucial to comprehend the genesis and evolution of multidrug-resistant bacteria. With this purpose, we designed an experimental evolution using Haemophilus influenzae RdKW20 as the model strain carrying the ColE1-like plasmid pB1000. Five H. influenzae populations adapted previously to the culture conditions were transformed with pB1000 and subsequently evolved to compensate for the plasmid-associated fitness cost. Afterward, we performed an integrative multiomic analysis combining genomics, transcriptomics, and metabolomics to explore the molecular mechanisms involved in the compensatory evolution of the plasmid. Our results demonstrate that minimal modifications in the host are responsible for plasmid adaptation. Among all of them, the most enriched process was amino acid metabolism, especially those pathways related to serine, tryptophan, and arginine, eventually related to the genesis and resolution of plasmid dimers. Additional rearrangements occurred during the plasmid adaptation, such as an overexpression of the ribonucleotide reductases and metabolic modifications within specific membrane phospholipids. All these findings demonstrate that the plasmid compensation occurs through the combination of diverse host-mediated mechanisms, of which some are beyond genomic and transcriptomic modifications. IMPORTANCE The ability of bacteria to horizontally transfer genetic material has turned antimicrobial resistance into one of the major sanitary crises of the 21st century. Plasmid conjugation is considered the main mechanism responsible for the mobilization of resistance genes, and its understanding is crucial to tackle this crisis. It is generally accepted that the acquisition and maintenance of mobile genetic elements entail a fitness cost to its host, which is susceptible to be alleviated through a coadaptation process or compensatory evolution. Notwithstanding, despite recent major efforts, the underlying mechanisms involved in this adaptation remain poorly characterized. Analyzing the plasmid/host coadaptation from a multiomic perspective sheds light on the physiological processes involved in the compensation, providing a new understanding on the genesis and evolution of plasmid-mediated antimicrobial-resistant bacteria.