Integrated gut metabolome and microbiome fingerprinting reveals that dysbiosis precedes allergic inflammation in IgE-mediated pediatric cow's milk allergy.

BACKGROUND: IgE-mediated cow's milk allergy (IgE-CMA) is one of the first allergies to arise in early childhood and may result from exposure to various milk allergens, of which ß-lactoglobulin (BLG) and casein are the most important. Understanding the underlying mechanisms behind IgE-CMA is imperative for the discovery of novel biomarkers and the design of innovative treatment and prevention strategies. METHODS: We report a longitudinal in vivo murine model, in which two mice strains (BALB/c and C57Bl/6) were sensitized to BLG using either cholera toxin or an oil emulsion (n = 6 per group). After sensitization, mice were challenged orally, their clinical signs monitored, antibody (IgE and IgG1) and cytokine levels (IL-4 and IFN-γ) measured, and fecal samples subjected to metabolomics. The results of the murine models were further extrapolated to fecal microbiome-metabolome data from our population of IgE-CMA (n = 22) and healthy (n = 23) children (Trial: NCT04249973), on which polar metabolomics, lipidomics and 16S rRNA metasequencing were performed. In vitro gastrointestinal digestions and multi-omics corroborated the microbial origin of proposed metabolic changes. RESULTS: During mice sensitization, we observed multiple microbially derived metabolic alterations, most importantly bile acid, energy and tryptophan metabolites, that preceded allergic inflammation. We confirmed microbial dysbiosis, and its associated effect on metabolic alterations in our patient cohort, through in vitro digestions and multi-omics, which was accompanied by metabolic signatures of low-grade inflammation. CONCLUSION: Our results indicate that gut dysbiosis precedes allergic inflammation and nurtures a chronic low-grade inflammation in children on elimination diets, opening important new opportunities for future prevention and treatment strategies.

Palmitic acid sophorolipid biosurfactant: from self-assembled fibrillar network (SAFiN) to hydrogels with fast recovery.

Nanofibres are an interesting phase into which amphiphilic molecules can self-assemble. Described for a large number of synthetic lipids, they were seldom reported for natural lipids like microbial amphiphiles, known as biosurfactants. In this work, we show that the palmitic acid congener of sophorolipids (SLC16:0), one of the most studied families of biosurfactants, spontaneously forms a self-assembled fibre network (SAFiN) at pH below 6 through a pH jump process. pH-resolved in situ small-angle X-ray scattering (SAXS) shows a continuous micelle-to-fibre transition, characterized by an enhanced core-shell contrast between pH 9 and pH 7 and micellar fusion into a flat membrane between pH 7 and pH 6, approximately. Below pH 6, homogeneous, infinitely long nanofibres form by peeling off the membranes. Eventually, the nanofibre network spontaneously forms a thixotropic hydrogel with fast recovery rates after applying an oscillatory strain amplitude out of the linear viscoelastic regime: after being submitted to strain amplitudes during 5 min, the hydrogel recovers about 80% and 100% of its initial elastic modulus after, respectively, 20 s and 10 min. Finally, the strength of the hydrogel depends on the medium's final pH, with an elastic modulus fivefold higher at pH 3 than at pH 6. This article is part of the theme issue 'Bio-derived and bioinspired sustainable advanced materials for emerging technologies (part 1)'.

Novel Alkaloids from Marine Actinobacteria: Discovery and Characterization.

The marine environment is an excellent resource for natural products with therapeutic potential. Its microbial inhabitants, often associated with other marine organisms, are specialized in the synthesis of bioactive secondary metabolites. Similar to their terrestrial counterparts, marine Actinobacteria are a prevalent source of these natural products. Here, we discuss 77 newly discovered alkaloids produced by such marine Actinobacteria between 2017 and mid-2021, as well as the strategies employed in their elucidation. While 12 different classes of alkaloids were unraveled, indoles, diketopiperazines, glutarimides, indolizidines, and pyrroles were most dominant. Discoveries were mainly based on experimental approaches where microbial extracts were analyzed in relation to novel compounds. Although such experimental procedures have proven useful in the past, the methodologies need adaptations to limit the chance of compound rediscovery. On the other hand, genome mining provides a different angle for natural product discovery. While the technology is still relatively young compared to experimental screening, significant improvement has been made in recent years. Together with synthetic biology tools, both genome mining and extract screening provide excellent opportunities for continued drug discovery from marine Actinobacteria.

Production of long-chain hydroxy fatty acids by Starmerella bombicola.

To decrease our dependency for the diminishing source of fossils resources, bio-based alternatives are being explored for the synthesis of commodity and high-value molecules. One example in this ecological initiative is the microbial production of the biosurfactant sophorolipids by the yeast Starmerella bombicola. Sophorolipids are surface-active molecules mainly used as household and laundry detergents. Because S. bombicola is able to produce high titers of sophorolipids, the yeast is also used to increase the portfolio of lipophilic compounds through strain engineering. Here, the one-step microbial production of hydroxy fatty acids by S. bombicola was accomplished by the selective blockage of three catabolic pathways through metabolic engineering. Successful production of 17.39 g/l (ω-1) linked hydroxy fatty acids was obtained by the successive blockage of the sophorolipid biosynthesis, the ß-oxidation and the ω-oxidation pathways. Minor contamination of dicarboxylic acids and fatty aldehydes were successfully removed using flash chromatography. This way, S. bombicola was further expanded into a flexible production platform of economical relevant compounds in the chemical, food and cosmetic industries.

Starmerella bombicola, an industrially relevant, yet fundamentally underexplored yeast.

In this review, we focus on one of the most important microbial producers of biosurfactants, Starmerella bombicola. Emphasis is laid on the discovery, taxonomy, habitat, cellular characteristics, biochemistry and genetics of this non-pathogenic yeast. Biosurfactants are natural surface-active compounds produced by several types of microorganisms and have been considered an interesting alternative to synthetic surfactants. The sophorolipids produced by S. bombicola are promising biosurfactants, with application potential in food, pharmaceutical, cosmetic and cleaning industries. The fundamental knowledge described in this review is of crucial interest to optimize production of these promising compounds. Furthermore, it can be translated to produce novel non-native bioactive molecules with S. bombicola, and to deepen fundamental knowledge on other non-conventional yeast species and in the end to broaden their application potential as well.

Multivariate versus machine learning-based classification of rapid evaporative Ionisation mass spectrometry spectra towards industry based large-scale fish speciation.

Detection and prevention of fish food fraud are of ever-increasing importance, prompting the need for rapid, high-throughput fish speciation techniques. Rapid Evaporative Ionisation Mass Spectrometry (REIMS) has quickly established itself as a powerful technique for the instant in situ analysis of foodstuffs. In the current study, a total of 1736 samples (2015-2021) - comprising 17 different commercially valuable fish species - were analysed using iKnife-REIMS, followed by classification with various multivariate and machine learning strategies. The results demonstrated that multivariate models, i.e. PCA-LDA and (O)PLS-DA, delivered accuracies from 92.5 to 100.0%, while RF and SVM-based classification generated accuracies from 88.7 to 96.3%. Real-time recognition on a separate test set of 432 samples (2022) generated correct speciation between 89.6 and 99.5% for the multivariate models, while the ML models underperformed (22.3-95.1%), in particular for the white fish species. As such, we propose a real-time validated modelling strategy using directly amenable PCA-LDA for rapid industry-proof large-scale fish speciation.

Exploration and optimization of extraction, analysis and data normalization strategies for mass spectrometry-based DNA adductome mapping and modeling.

Although interest in characterizing DNA damage by means of DNA adductomics has substantially grown, the field of DNA adductomics is still in its infancy, with room for optimization of methods for sample analysis, data processing and DNA adduct identification. In this context, the first objective of this study was to evaluate the use of hydrophilic interaction (HILIC) vs. reversed phase liquid chromatography (RPLC) coupled to high resolution mass spectrometry (HRMS) and thermal acidic vs. enzymatic hydrolysis of DNA followed by DNA adduct purification and enrichment using solid-phase extraction (SPE) or fraction collection for DNA adductome mapping. The second objective was to assess the use of total ion count (TIC) and median intensity (MedI) normalization compared to QC (quality control), iQC (internal QC) and quality control-based robust locally estimated scatterplot smoothing (LOESS) signal correction (QC-RLSC) normalization for processing of the acquired data. The results demonstrate that HILIC compared to RPLC allowed better modeling of the tentative DNA adductome, particularly in combination with thermal acidic hydrolysis and SPE (more valid models, with an average Q2(Y) and R2(Y) of 0.930 and 0.998, respectively). Regarding the need for data normalization and the management of (limited) system instability and signal drift, QC normalization outperformed TIC, MedI, iQC and LOESS normalization. As such, QC normalization can be put forward as the default data normalization strategy. In case of momentous signal drift and/or batch effects however, comparison to other normalization strategies (like e.g. LOESS) is recommended. In future work, further optimization of DNA adductomics may be achieved by merging of HILIC and RPLC datasets and/or application of 2D-LC, as well as the inclusion of Schiff base stabilization and/or fraction collection in the thermal acidic hydrolysis-SPE sample preparation workflow.

Comprehensive metabolomics reveals correlation between sophorolipid biosynthesis and autophagy.

Sophorolipids are biobased and biodegradable glycolipid surface-active agents contributing to the shift from petroleum to biobased surfactants, associated with clear environmental benefits. However, their production cost is currently too high to allow commercialisation. Therefore, a continuous sophorolipid production process was evaluated, i.e., a retentostat with an external filtration unit. Despite an initial increase in volumetric productivity, productivity eventually declined to almost 0 g L-1 h-1. Following comprehensive metabolomics on supernatant obtained from a standardised retentostat, we hypothesised exhaustion of the N-starvation-induced autophagy as the main mechanism responsible for the decline in bolaform sophorolipid productivity. Thirty-six metabolites that correlate with RNA/protein autophagy and high sophorolipid productivity were putatively identified. In conclusion, our results unveil a plausible cause of this bola sophorolipid productivity decline in an industrially relevant bioreactor set-up, which may thus impact majorly on future yeast biosurfactant regulation studies and the finetuning of bola sophorolipid production processes.

Point-of-care applicable metabotyping using biofluid-specific electrospun MetaSAMPs directly amenable to ambient LA-REIMS.

In recent years, ambient ionization mass spectrometry (AIMS) including laser ablation rapid evaporation IMS, has enabled direct biofluid metabolome analysis. AIMS procedures are, however, still hampered by both analytical, i.e., matrix effects, and practical, i.e., sample transport stability, drawbacks that impede metabolome coverage. In this study, we aimed at developing biofluid-specific metabolome sampling membranes (MetaSAMPs) that offer a directly applicable and stabilizing substrate for AIMS. Customized rectal, salivary, and urinary MetaSAMPs consisting of electrospun (nano)fibrous membranes of blended hydrophilic (polyvinylpyrrolidone and polyacrylonitrile) and lipophilic (polystyrene) polymers supported metabolite absorption, adsorption, and desorption. Moreover, MetaSAMP demonstrated superior metabolome coverage and transport stability compared to crude biofluid analysis and was successfully validated in two pediatric cohorts (MetaBEAse, n = 234 and OPERA, n = 101). By integrating anthropometric and (patho)physiological with MetaSAMP-AIMS metabolome data, we obtained substantial weight-driven predictions and clinical correlations. In conclusion, MetaSAMP holds great clinical application potential for on-the-spot metabolic health stratification.

Rapid ex vivo molecular fingerprinting of biofluids using laser-assisted rapid evaporative ionization mass spectrometry.

Of the many metabolites involved in any clinical condition, only a narrow range of biomarkers is currently being used in the clinical setting. A key to personalized medicine would be to extend this range. Metabolic fingerprinting provides a more comprehensive insight, but many methods used for metabolomics analysis are too complex and time-consuming to be diagnostically useful. Here, a rapid evaporative ionization mass spectrometry (REIMS) system for direct ex vivo real-time analysis of biofluids with minor sample pretreatment is detailed. The REIMS can be linked to various laser wavelength systems (such as optical parametric oscillator or CO2 laser) and with automation for high-throughput analysis. Laser-induced sample evaporation occurs within seconds through radiative heating with the plume guided to the MS instrument. The presented procedure includes (i) laser setup with automation, (ii) analysis of biofluids (blood/urine/stool/saliva/sputum/breast milk) and (iii) data analysis. We provide the optimal settings for biofluid analysis and quality control, enabling sensitive, precise and robust analysis. Using the automated setup, 96 samples can be analyzed in ~35-40 min per ionization mode, with no intervention required. Metabolic fingerprints are made up of 2,000-4,000 features, for which relative quantification can be achieved at high repeatability when total ion current normalization is applied. With saliva and feces as example matrices, >70% of features had a coefficient of variance ≤30%. However, to achieve acceptable long-term reproducibility, additional normalizations by, e.g., LOESS are recommended, especially for positive ionization.

Impact of storage conditions on the human stool metabolome and lipidome: Preserving the most accurate fingerprint.

Faecal metabolomics markedly emerged in clinical as well as analytical chemistry through the unveiling of aberrations in metabolic signatures as reflection of variance in gut (patho)physiology and beyond. Logistic hurdles, however, hinder the analysis of stool samples immediately following collection, inferring the need of biobanking. Yet, the optimum way of storing stool material remains to be determined, in order to conserve an accurate snapshot of the metabolome and circumvent artifacts regarding the disease and parameter(s) under observation. To address this problem, this study scrutinised the impact of freeze-thaw cycling, storage duration, temperature and aerobicity, thereby using ultra-high performance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS)-based polar metabolomics and lipidomics methodologies for faecal metabolomics. Both targeted (n > 400) and untargeted approaches were implemented to assess storage effects on individual chemical classes of metabolites as well as the faecal fingerprint. In general, recommendations are that intact stool samples should be divided into aliquots, lyophilised and stored at -80 °C for a period no longer than 18 weeks, and avoiding any freeze-thawing. The first preservation week exerted the most decisive impact regarding storage temperature, i.e. 12.1% and 6.4% of the polar metabolome experienced a shift at -20 °C and at -80 °C, respectively, whereas 8.6% and 7.9% was observed to be changed significantly for the lipidome. In addition, aside from the negligible impact of aerobicity, the polar metabolome appeared to be more dependent on the storage conditions applied compared to the lipidome, which emerged as the more stable fraction when assessing the storage duration for 25 weeks. If the interest would greatly align with particular chemical classes, such as branched-chain amino acids or short-chain fatty acids, specific storage duration recommendations are reported. The provided insights on the stability of the faecal metabolome may contribute to a more reasoned design of experiments in biomarker detection or pathway elucidation within the field of faecal metabolomics.

Transformation of an Exotic Yeast Species into a Platform Organism: A Case Study for Engineering Glycolipid Production in the Yeast Starmerella bombicola.

In this chapter, a step-by-step approach on how to transform non-conventional yeasts or fungi into platform organisms is described. The non-conventional glycolipid producing yeast Starmerella bombicola (and in some cases also Pseudohyphozyma bogoriensis) is used as a case study. And more specifically how to engineer it toward production of new-to-nature glycolipids like bola sophorolipids. When starting genetic engineering efforts for non-lab strains, one should start at the very basis: identifying selection markers and possibly developing auxotrophic strains. Once this is done, the quest for the development of an optimal transformation method can be started. After optimization thereof, knock-out and knock-in strains can be generated based upon the specific strategy/aim. Sometimes this can lead to unexpected, but yet very interesting findings. To fully and efficiently expand the potential as a production platform of these yeast strains, a range of additional molecular tools are required. A well-equipped molecular toolbox should contain a set of characterized promotors, terminators, and defined genomic landing paths. The availability of an episomal system greatly facilitates engineering and screening efforts, but also offers the possibility of developing more advanced engineering techniques such as Crispr-Cas. InBio.be is a world leading pioneer to do this for the yeast S. bombicola and combined, these efforts will result in the commercialization of new types of glycolipids in the next few years.