Dearomatization drives complexity generation in freshwater organic matter.

Dissolved organic matter (DOM) is one of the most complex, dynamic and abundant sources of organic carbon, but its chemical reactivity remains uncertain1-3. Greater insights into DOM structural features could facilitate understanding its synthesis, turnover and processing in the global carbon cycle4,5. Here we use complementary multiplicity-edited 13C nuclear magnetic resonance (NMR) spectra to quantify key substructures assembling the carbon skeletons of DOM from four main Amazon rivers and two mid-size Swedish boreal lakes. We find that one type of reaction mechanism, oxidative dearomatization (ODA), widely used in organic synthetic chemistry to create natural product scaffolds6-10, is probably a key driver for generating structural diversity during processing of DOM that are rich in suitable polyphenolic precursor molecules. Our data suggest a high abundance of tetrahedral quaternary carbons bound to one oxygen and three carbon atoms (OCqC3 units). These units are rare in common biomolecules but could be readily produced by ODA of lignin-derived and tannin-derived polyphenols. Tautomerization of (poly)phenols by ODA creates non-planar cyclohexadienones, which are subject to immediate and parallel cycloadditions. This combination leads to a proliferation of structural diversity of DOM compounds from early stages of DOM processing, with an increase in oxygenated aliphatic structures. Overall, we propose that ODA is a key reaction mechanism for complexity acceleration in the processing of DOM molecules, creation of new oxygenated aliphatic molecules and that it could be prevalent in nature.

Discovery of Glycation Products: Unraveling the Unknown Glycation Space Using a Mass Spectral Library from In Vitro Model Systems.

The nonenzymatic reaction between amino acids (AAs) and reducing sugars, also known as the Maillard reaction, is the primary source of free glycation products (GPs) in vivo and in vitro. The limited number of MS/MS records for GPs in public libraries hinders the annotation and investigation of nonenzymatic glycation. To address this issue, we present a mass spectral library containing the experimental MS/MS spectra of diverse GPs from model systems. Based on the conceptional reaction processes and structural characteristics of products, we classified GPs into common GPs (CGPs) and modified AAs (MAAs). A workflow for annotating GPs was established based on the structural and fragmentation patterns of each GP type. The final spectral library contains 157 CGPs, 499 MAAs, and 2426 GP spectra with synthetic model system information, retention time, precursor m/z, MS/MS, and annotations. As a proof-of-concept, we demonstrated the use of the library for screening GPs in unidentified spectra of human plasma and urine. The AAs with the C6H10O5 modification, fructosylation from Amadori rearrangement, were the most found GPs. With the help of the model system, we confirmed the existence of C6H10O5-modified Valine in human plasma by matching both retention time, MS1, and MS/MS without reference standards. In summary, our GP library can serve as an online resource to quickly screen possible GPs in an untargeted metabolomics workflow, furthermore with the model system as a practical synthesis method to confirm their identity.

DBDIpy: a Python library for processing of untargeted datasets from real-time plasma ionization mass spectrometry.

MOTIVATION: Plasma ionization is rapidly gaining popularity for mass spectrometry (MS)-based studies of volatiles and aerosols. However, data from plasma ionization are delicate to interpret as competing ionization pathways in the plasma create numerous ion species. There is no tool for detection of adducts and in-source fragments from plasma ionization data yet, which makes data evaluation ambiguous. SUMMARY: We developed DBDIpy, a Python library for processing and formal analysis of untargeted, time-sensitive plasma ionization MS datasets. Its core functionality lies in the identification of in-source fragments and identification of rivaling ionization pathways of the same analytes in time-sensitive datasets. It further contains elementary functions for processing of untargeted metabolomics data and interfaces to an established ecosystem for analysis of MS data in Python. AVAILABILITY AND IMPLEMENTATION: DBDIpy is implemented in Python (Version ≥ 3.7) and can be downloaded from PyPI the Python package repository (https://pypi.org/project/DBDIpy) or from GitHub (https://github.com/leopold-weidner/DBDIpy). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Asthma-protective agents in dust from traditional farm environments.

BACKGROUND: Growing up on traditional European or US Amish dairy farms in close contact with cows and hay protects children against asthma, and airway administration of extracts from dust collected from cowsheds of those farms prevents allergic asthma in mice. OBJECTIVES: This study sought to begin identifying farm-derived asthma-protective agents. METHODS: Our work unfolded along 2 unbiased and independent but complementary discovery paths. Dust extracts (DEs) from protective and nonprotective farms (European and Amish cowsheds vs European sheep sheds) were analyzed by comparative nuclear magnetic resonance profiling and differential proteomics. Bioactivity-guided size fractionation focused on protective Amish cowshed DEs. Multiple in vitro and in vivo functional assays were used in both paths. Some of the proteins thus identified were characterized by in-solution and in-gel sodium dodecyl sulfate-polyacrylamide gel electrophoresis enzymatic digestion/peptide mapping followed by liquid chromatography/mass spectrometry. The cargo carried by these proteins was analyzed by untargeted liquid chromatography-high-resolution mass spectrometry. RESULTS: Twelve carrier proteins of animal and plant origin, including the bovine lipocalins Bos d 2 and odorant binding protein, were enriched in DEs from protective European cowsheds. A potent asthma-protective fraction of Amish cowshed DEs (≈0.5% of the total carbon content of unfractionated extracts) contained 7 animal and plant proteins, including Bos d 2 and odorant binding protein loaded with fatty acid metabolites from plants, bacteria, and fungi. CONCLUSIONS: Animals and plants from traditional farms produce proteins that transport hydrophobic microbial and plant metabolites. When delivered to mucosal surfaces, these agents might regulate airway responses.

Lipidomic and Metallomic Alteration of Caenorhabditis elegans after Acute and Chronic Manganese, Iron, and Zinc Exposure with a Link to Neurodegenerative Disorders.

Parkinson's disease (PD) progresses with the loss of dopaminergic neurons in the substantia nigra pars compacta region of the brain. The superior mechanisms and the cause of this specific localized neurodegeneration is currently unknown. However, experimental evidence indicates a link between PD progression and reactive oxygen species with imbalanced metal homeostasis. Wild-type Caenorhabditis elegans exposed to redox-active metals was used as the model organism to study cellular response to imbalanced metal homeostasis linked to neurodegenerative diseases. Using modern hyphenated techniques such as capillary electrophoresis coupled to inductively coupled plasma mass spectrometry and ultrahigh-performance liquid chromatography mass spectrometry, alterations in the lipidome and metallome were determined in vivo. In contrast to iron, most of the absorbed zinc and manganese were loosely bound. We observed changes in the phospholipid composition for acute iron and manganese exposures, as well as chronic zinc exposure. Furthermore, we focused on the mitochondrial membrane alteration due to its importance in neuronal function. However, significant changes in the inner mitochondrial membrane by determination of cardiolipin species could only be observed for acute iron exposure. These results indicate different intracellular sites of local ROS generation, depending on the redox active metal. Our study combines metallomic and lipidomic alterations as the cause and consequence to enlighten intracellular mechanisms in vivo, associated with PD progression. The mass spectrometry raw data have been deposited to the MassIVE database (https://massive.ucsd.edu) with the identifier MSV000090796 and 10.25345/C51J97C8F.

Rebuilding core abscisic acid signaling pathways of Arabidopsis in yeast.

The phytohormone abscisic acid (ABA) regulates plant responses to abiotic stress, such as drought and high osmotic conditions. The multitude of functionally redundant components involved in ABA signaling poses a major challenge for elucidating individual contributions to the response selectivity and sensitivity of the pathway. Here, we reconstructed single ABA signaling pathways in yeast for combinatorial analysis of ABA receptors and coreceptors, downstream-acting SnRK2 protein kinases, and transcription factors. The analysis shows that some ABA receptors stimulate the pathway even in the absence of ABA and that SnRK2s are major determinants of ABA responsiveness by differing in the ligand-dependent control. Five SnRK2s, including SnRK2.4 known to be active under osmotic stress in plants, activated ABA-responsive transcription factors and were regulated by ABA receptor complexes in yeast. In the plant tissue, SnRK2.4 and ABA receptors competed for coreceptor interaction in an ABA-dependent manner consistent with a tight integration of SnRK2.4 into the ABA signaling pathway. The study establishes the suitability of the yeast system for the dissection of core signaling cascades and opens up future avenues of research on ligand-receptor regulation.

Real-Time Monitoring of Miniaturized Thermal Food Processing by Advanced Mass Spectrometric Techniques.

Mass spectrometry is a popular and powerful analytical tool to study the effects of food processing. Industrial sampling, real-life sampling, or challenging academic research on process-related volatile and aerosol research often demand flexible, time-sensitive data acquisition by state-of-the-art mass analyzers. Here, we show a laboratory-scaled, miniaturized, and highly controllable setup for the online monitoring of aerosols and volatiles from thermal food processing based on dielectric barrier discharge ionization (DBDI) mass spectrometry (MS). We demonstrate the opportunities offered by the setup from a foodomics perspective to study emissions from the thermal processing of wheat bread rolls at 210 °C by Fourier transformation ion cyclotron resonance MS. As DBDI is an emerging technology, we compared its ionization selectivity to established atmospheric pressure ionization tools: we found DBDI preferably ionizes saturated, nitrogenous compounds. We likewise identified a sustainable overlap in the selectivity of detected analytes with APCI and electrospray ionization (ESI). Further, we dynamically recorded chemical fingerprints throughout the thermal process. Unsupervised classification of temporal response patterns was used to describe the dynamic nature of the reaction system. Compared to established tools for real-time MS, our setup permits one to monitor chemical changes during thermal food processing at ultrahigh resolution, establishing an advanced perspective for real-time mass spectrometric analysis of food processing.

Selectivity of ß-Cyclodextrin Polymer toward Aquatic Contaminants: Insights from Ultrahigh-Resolution Mass Spectrometry of Dissolved Organic Matter.

Selectivity in solid-phase extraction (SPE) materials has become increasingly important for analyte enrichment in sensitive analytical workflows to alleviate detrimental matrix effects. Molecular-level investigation of matrix constituents, which are preferentially extracted or excluded, can provide the analytical chemist with valuable information to learn about their control on sorbent selectivity. In this work, we employ nontargeted Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) to elucidate the molecular chemodiversity of freshwater-derived dissolved organic matter (DOM) extracted by the selective model sorbent ß-cyclodextrin polymer (ß-CDP) in comparison to conventional, universal SPE sorbents (i.e., Oasis HLB, Supel-Select HLB, and LiChrolut EN). Statistical analysis of MS data corroborated the highly selective nature of ß-CDP by revealing the extracted DOM spectra that are most dissimilar to original compositions. We found that its selectivity was characterized by pronounced discrimination against highly oxygenated and unsaturated DOM compounds, which were associated with the classes of lignin-like, tannin-like, and carboxylic-rich alicyclic molecules. In contrast, conventional sorbents excluded less highly oxygenated compounds and showed a more universal extraction behavior for a wide range of DOM compositional space. We lay these findings in a larger context that aids the analyst in obtaining an a priori estimate of sorbent selectivity toward any target analyte of interest serving thereby an optimization of sample preparation. This study highlights the great value of nontargeted ultrahigh-resolution MS for better understanding of targeted analytics and provides new insights into the selective sorption behavior of novel sorbents.

Discriminative Behavior of Cyclodextrin Polymers against Dissolved Organic Matter: Role of Cavity Size and Sorbate Properties.

Cyclodextrin polymers (CDPs) are promising next-generation adsorbents in water purification technologies. The selectivity of the polymer derivate cross-linked with tetrafluoroterephthalonitrile (TFN-CDP) for nonionic and cationic micropollutants (MPs) over dissolved organic matter (DOM) renders the adsorbent also attractive for many analytical applications. The molecular drivers of the observed selectivity are, nonetheless, not yet fully understood. To provide new insights into the sorption mechanism, we (i) synthesized TFN-CDPs with different cavity sizes (α-, ß-, γ-CDP); (ii) assessed their extraction efficiencies for selected nonionic MPs in competition with different DOM size fractions (<1, 1-3, 3-10, >10 kDa) to test for size-selectivity; and (iii) performed nontargeted, ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry analysis on CDP-extracted DOM compounds (<1 kDa) to probe for molecular sorbate properties governing their selective sorption. First, no evidence of size-selectivity was obtained through either the different CD cavity sizes (i) or the two independent approaches (ii) and (iii). Second, we found a dominant impact of sorbate oxygenation and polarity on the extraction of DOM and MPs, respectively, with relatively oxygen-poor/nonpolar molecules favorably retained on all α-, ß-, and γ-CDP. Third, our data indicates exclusion of an anionic matrix, such as carboxylic acids, but preferential sorption of cationic nitrogen-bearing DOM, pointing at repulsive and attractive forces with the negatively charged cross-linker as a likely reason. Therefore, we ascribe TFN-CDP's selectivity to nonpolar and electrostatic interactions between MPs/DOM and the polymer building blocks. These molecular insights can further aid in the optimization of efficient and selective sorbent design for environmental and analytical applications.

MobilityTransformR: an R package for effective mobility transformation of CE-MS data.

SUMMARY: We present MobilityTransformR, an R/Bioconductor package for the effective mobility scaling of capillary zone electrophoresis-mass spectrometry (CE-MS) data. It uses functionality from different R packages that are frequently used for data processing and analysis in MS-based metabolomics workflows, allowing the subsequent use of reproducible transformed CE-MS data in existing workflows. AVAILABILITY AND IMPLEMENTATION: MobilityTransformR is implemented in R (Version >= 4.2) and can be downloaded directly from the Bioconductor database (https://bioconductor.org/packages/MobilityTransformR) or GitHub (https://github.com/LiesaSalzer/MobilityTransformR). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Capillary electrophoresis-mass spectrometry as a tool for Caenorhabditis elegans metabolomics research.

INTRODUCTION: Polar metabolites in Caenorhabditis elegans (C. elegans) have predominantly been analyzed using hydrophilic interaction liquid chromatography coupled to mass spectrometry (HILIC-MS). Capillary electrophoresis coupled to mass spectrometry (CE-MS) represents another complementary analytical platform suitable for polar and charged analytes. OBJECTIVE: We compared CE-MS and HILIC-MS for the analysis of a set of 60 reference standards relevant for C. elegans and specifically investigated the strengths of CE separation. Furthermore, we employed CE-MS as a complementary analytical approach to study polar metabolites in C. elegans samples, particularly in the context of longevity, in order to address a different part of its metabolome. METHOD: We analyzed 60 reference standards as well as metabolite extracts from C. elegans daf-2 loss-of-function mutants and wild-type (WT) samples using HILIC-MS and CE-MS employing a Q-ToF-MS instrument. RESULTS: CE separations showed narrower peak widths and a better linearity of the estimated response function across different concentrations which is linked to less saturation of the MS signals. Additionally, CE exhibited a distinct selectivity in the separation of compounds compared to HILIC-MS, providing complementary information for the analysis of the target compounds. Analysis of C. elegans metabolites of daf-2 mutants and WT samples revealed significant alterations in shared metabolites identified through HILIC-MS, as well as the presence of distinct metabolites. CONCLUSION: CE-MS was successfully applied in C. elegans metabolomics, being able to recover known as well as identify novel putative biomarkers of longevity.

Open Search of Peptide Glycation Products from Tandem Mass Spectra.

Identification of chemically modified peptides in mass spectrometry (MS)-based glycation studies is a crucial yet challenging task. There is a need to establish a mode for matching tandem mass spectrometry (MS/MS) data, allowing for both known and unknown peptide glycation modifications. We present an open search approach that uses classic and modified peptide fragment ions. The latter are shifted by the mass delta of the modification. Both provide key structural information that can be used to assess the peptide core structure of the glycation product. We also leverage redundant neutral losses from the modification side chain, introducing a third ion class for matching referred to as characteristic fragment ions. We demonstrate that peptide glycation product MS/MS spectra contain multidimensional information and that most often, more than half of the spectral information is ignored if no attempt is made to use a multi-step matching algorithm. Compared to regular and/or modified peptide ion matching, our triple-ion strategy significantly increased the median interpretable fraction of the glycation product MS/MS spectra. For reference, we apply our approach for Amadori product characterization and identify all established diagnostic ions automatically. We further show how this method effectively applies the open search concept and allows for optimized elucidation of unknown structures by presenting two hitherto undescribed peptide glycation modifications with a delta mass of 102.0311 and 268.1768 Da. We characterize their fragmentation signature by integration with isotopically labeled glycation products, which provides high validity for non-targeted structure identification.

Feature Selection Pipelines with Classification for Non-targeted Metabolomics Combining the Neural Network and Genetic Algorithm.

Non-targeted metabolomics via high-resolution mass spectrometry methods, such as direct infusion Fourier transform-ion cyclotron resonance mass spectrometry (DI-FT-ICR MS), produces data sets with thousands of features. By contrast, the number of samples is in general substantially lower. This disparity presents challenges when analyzing non-targeted metabolomics data sets and often requires custom methods to uncover information not always accessible via classical statistical techniques. In this work, we present a pipeline that combines a convolutional neural network with traditional statistical approaches and an adaptation of a genetic algorithm. The developed method was applied to a lifestyle intervention cohort data set, where subjects at risk of type 2 diabetes underwent an oral glucose tolerance test. Feature selection is the final result of the pipeline, achieved through classification of the data set via a neural network, with a precision-recall score of over 0.9 on the test set. The features most relevant for the described classification were then chosen via a genetic algorithm. The output of the developed pipeline encompasses approximately 200 features with high predictive scores, providing a fingerprint of the metabolic changes in the prediabetic class on the data set. Our framework presents a new approach which allows to apply complex modeling based on convolutional neural networks for the analysis of high-resolution mass spectrometric data.

Dihydrogen phosphate anion boosts the detection of sugars in electrospray ionization mass spectrometry: A combined experimental and computational investigation.

RATIONALE: Sugars are key molecules of life but challenging to detect via electrospray ionization mass spectrometry (ESI-MS). Unfortunately, sugars are challenging analytes for mass spectrometric methods due to their high gas-phase deprotonation energies and low gas-phase proton affinities which make them difficult to ionize in high abundance for MS detection. METHODS: Hydrogen-bond interactions in H2 PO4 - -saccharide anionic systems were studied both experimentally (via electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry, ESI-FT-ICR-MS) and computationally by several sophisticated density-functional theoretical methods (DFT and DFT-D3). RESULTS: The H2 PO4 - dopant boosts the detection of sugars up to 51-times in the case of sucrose and up to 263-times for glucose (at 0.1 ppm concentration level). H2 PO4 - binds toward sugar molecules with noticeably more hydrogen bonds than the established dopant chloride Cl- does, with increasing binding energies in the order: Monosaccharides < Trisaccharides < Disaccharides. Analysis of a complex oak plant sample revealed that NH4 H2 PO4 specifically labeled a diverse set of sugar-type plant metabolites in the form of [M + H2 PO4 ]- complexes. CONCLUSIONS: We reveal the mechanism of interaction of H2 PO4 - with different sugars and glycosylated organic compounds, which significantly enhances their ionization in mass spectrometry. A computational and experimental investigation is presented. A strong correlation between the MS signal intensities of detected [M + H2 PO4 ]- anions of different saccharides and their calculated dissociation enthalpies was revealed. Thus, the variation in MS signal intensities can be very well described to a large extent by the variation in calculated saccharide affinities toward the H2 PO4 - dopant anion, showing that DFT-D3 can very well describe experimental FT-ICR-MS observations.

An Overview of the Latest Metabolomics Studies on Atopic Eczema with New Directions for Study.

Atopic eczema (AE) is an inflammatory skin disorder affecting approximately 20% of children worldwide and early onset can lead to asthma and allergies. Currently, the mechanisms of the disease are not fully understood. Metabolomics, the analysis of small molecules in the skin produced by the host and microbes, opens a window to observe the mechanisms of the disease which then may lead to new drug targets for AE treatment. Here, we review the latest advances in AE metabolomics, highlighting both the lipid and non-lipid molecules, along with reviewing the metabolites currently known to reside in the skin.

Synthesis, Physicochemical Characterization, and Antibacterial Performance of Silver-Lactoferrin Complexes.

Antibiotic-resistant bacteria pose one of the major threats to human health worldwide. The issue is fundamental in the case of chronic wound treatment. One of the latest trends to overcome the problem is the search for new antibacterial agents based on silver. Thus, the aim of this research was to synthesize the silver-lactoferrin complex as a new generation of substances for the treatment of infected wounds. Moreover, one of the tasks was to investigate the formation mechanisms of the respective complexes and the influence of different synthesis conditions on the features of final product. The batch-sorption study was performed by applying the Langmuir and Freundlich isotherm models for the process description. Characterization of the complexes was carried out by spectroscopy, spectrometry, and separation techniques, as well as with electron microscopy. Additionally, the biological properties of the complex were evaluated, i.e., the antibacterial activity against selected bacteria and the impact on L929 cell-line viability. The results indicate the formation of a heterogeneous silver-lactoferrin complex that comprises silver nanoparticles. The complex has higher antibacterial strength than both native bovine lactoferrin and Ag+, while being comparable to silver toxicity.

Production and Characterization of a Novel Exopolysaccharide from Ramlibacter tataouinensis.

The current study examines the desiccation-resistant Ramlibacter tataouinensis TTB310T as a model organism for the production of novel exopolysaccharides and their structural features. This bacterium is able to produce dividing forms of cysts which synthesize cell-bound exopolysaccharide. Initial experiments were conducted on the enrichment of cyst biomass for exopolysaccharide production under batch-fed conditions in a pilot-scale bioreactor, with lactate as the source of carbon and energy. The optimized medium produced significant quantities of exopolysaccharide in a single growth phase, since the production of exopolysaccharide took place during the division of the cysts. The exopolysaccharide layer was extracted from the cysts using a modified trichloroacetic acid method. The biochemical characterization of purified exopolysaccharide was performed by gas chromatography, ultrahigh-resolution mass spectrometry, nuclear magnetic resonance, and Fourier-transform infrared spectrometry. The repeating unit of exopolysaccharide was a decasaccharide consisting of ribose, glucose, rhamnose, galactose, mannose, and glucuronic acid with the ratio 3:2:2:1:1:1, and additional substituents such as acetyl, succinyl, and methyl moieties were also observed as a part of the exopolysaccharide structure. This study contributes to a fundamental understanding of the novel structural features of exopolysaccharide from a dividing form of cysts, and, further, results can be used to study its rheological properties for various industrial applications.

The role of fecal sulfur metabolome in inflammatory bowel diseases.

Sulfur metabolism and sulfur-containing metabolites play an important role in the human digestive system, and sulfur compounds and pathways are associated with inflammatory bowel diseases (IBD). In fact, cysteine metabolism results in the production of taurine and sulfate, and gut microbes catabolize them into hydrogen sulfide, a signaling molecule with various biological functions. Besides metabolites originating from sulfur metabolism, several other sulfur-containing metabolites of different classes were detected in human feces, consisting of non-volatile and volatile compounds. Sulfated steroids and bile acids such as taurine-conjugated bile acids are the major classes along with sulfur amino acids and sulfur-containing peptides. Indeed, sulfur-containing metabolites were described in stool samples from healthy subjects, patients suffering from colorectal cancer or IBD. In metabolomics-driven studies, around 50 known sulfur-containing metabolites were linked to IBD. Taurine, taurocholic acid, taurochenodeoxycholic acid, methionine, methanethiol and hydrogen sulfide were regularly reported in IBD studies, and most of them were elevated in stool samples from IBD patients. We summarized from this review that there is strong interplay between perturbed gut microbiota in IBD, and the consistently higher abundance of sulfur-containing metabolites, which potentially represent substrates for sulfidogenic bacteria such as Bilophila or Escherichia and promote their growth. These bacteria might shift their metabolism towards the degradation of taurine and cysteine and therefore to a higher hydrogen sulfide production.

Ragweed plants grown under elevated CO2 levels produce pollen which elicit stronger allergic lung inflammation.

BACKGROUND: Common ragweed has been spreading as a neophyte in Europe. Elevated CO2 levels, a hallmark of global climate change, have been shown to increase ragweed pollen production, but their effects on pollen allergenicity remain to be elucidated. METHODS: Ragweed was grown in climate-controlled chambers under normal (380 ppm, control) or elevated (700 ppm, based on RCP4.5 scenario) CO2 levels. Aqueous pollen extracts (RWE) from control- or CO2 -pollen were administered in vivo in a mouse model for allergic disease (daily for 3-11 days, n = 5) and employed in human in vitro systems of nasal epithelial cells (HNECs), monocyte-derived dendritic cells (DCs), and HNEC-DC co-cultures. Additionally, adjuvant factors and metabolites in control- and CO2 -RWE were investigated using ELISA and untargeted metabolomics. RESULTS: In vivo, CO2 -RWE induced stronger allergic lung inflammation compared to control-RWE, as indicated by lung inflammatory cell infiltrate and mediators, mucus hypersecretion, and serum total IgE. In vitro, HNECs stimulated with RWE increased indistinctively the production of pro-inflammatory cytokines (IL-8, IL-1ß, and IL-6). In contrast, supernatants from CO2 -RWE-stimulated HNECs, compared to control-RWE-stimulated HNECS, significantly increased TNF and decreased IL-10 production in DCs. Comparable results were obtained by stimulating DCs directly with RWEs. The metabolome analysis revealed differential expression of secondary plant metabolites in control- vs CO2 -RWE. Mixes of these metabolites elicited similar responses in DCs as compared to respective RWEs. CONCLUSION: Our results indicate that elevated ambient CO2 levels elicit a stronger RWE-induced allergic response in vivo and in vitro and that RWE increased allergenicity depends on the interplay of multiple metabolites.

Transitory microbial habitat in the hyperarid Atacama Desert.

Traces of life are nearly ubiquitous on Earth. However, a central unresolved question is whether these traces always indicate an active microbial community or whether, in extreme environments, such as hyperarid deserts, they instead reflect just dormant or dead cells. Although microbial biomass and diversity decrease with increasing aridity in the Atacama Desert, we provide multiple lines of evidence for the presence of an at times metabolically active, microbial community in one of the driest places on Earth. We base this observation on four major lines of evidence: (i) a physico-chemical characterization of the soil habitability after an exceptional rain event, (ii) identified biomolecules indicative of potentially active cells [e.g., presence of ATP, phospholipid fatty acids (PLFAs), metabolites, and enzymatic activity], (iii) measurements of in situ replication rates of genomes of uncultivated bacteria reconstructed from selected samples, and (iv) microbial community patterns specific to soil parameters and depths. We infer that the microbial populations have undergone selection and adaptation in response to their specific soil microenvironment and in particular to the degree of aridity. Collectively, our results highlight that even the hyperarid Atacama Desert can provide a habitable environment for microorganisms that allows them to become metabolically active following an episodic increase in moisture and that once it decreases, so does the activity of the microbiota. These results have implications for the prospect of life on other planets such as Mars, which has transitioned from an earlier wetter environment to today's extreme hyperaridity.