Molecular analysis of broad-spectrum induced resistance in rice by the green leaf volatile Z-3-hexenyl acetate.

Green leaf volatiles (GLVs), volatile organic compounds released by plants upon tissue damage, are key signaling molecules in plant immunity. The ability of exogenous GLV application to trigger an induced resistance (IR) phenotype against arthropod pests has been widely reported, but its effectiveness against plant pathogens is less well understood. In this study, we combined mRNA sequencing-based transcriptomics and phytohormone measurements with multispectral imaging-based precision phenotyping to gain insights into the molecular basis of Z-3-hexenyl acetate-induced resistance (Z-3-HAC-IR) in rice. Furthermore, we evaluated the efficacy of Z-3-HAC-IR against a panel of economically significant rice pathogens: Pyricularia oryzae, Rhizoctonia solani, Xanthomonas oryzae pv. oryzae, Cochliobolus miyabeanus, and Meloidogyne graminicola. Our data revealed rapid induction of jasmonate metabolism and systemic induction of plant immune responses upon Z-3-HAC exposure, as well as a transient allocation cost due to accelerated chlorophyll degradation and nutrient remobilization. Z-3-HAC-IR proved effective against all tested pathogens except for C. miyabeanus, including against the (hemi)biotrophs M. graminicola, X. oryzae pv. oryzae, and P. oryzae. The Z-3-HAC-IR phenotype was lost in the jasmonate (JA)-deficient hebiba mutant, which confirms the causal role of JA in Z-3-HAC-IR. Together, our results show that GLV exposure in rice induces broad-spectrum, JA-mediated disease resistance with limited allocation costs, and may thus be a promising alternative crop protection approach.

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.

A multi-omics study to boost continuous bolaform sophorolipid production.

Biodegradable and biobased surface active agents are renewable and environmentally friendly alternatives to petroleum derived or oleochemical surfactants. However, they are accompanied by relatively high production costs. In this study, the aim was to reduce the production costs for an innovative type of microbial biosurfactant: bolaform sophorolipids, produced by the yeast Starmerella bombicola ΔsbleΔat. A novel continuous retentostat set-up was performed whereby continuous broth microfiltration retained the biomass in the bioreactor while performing an in situ product separation of bolaform sophorolipids. Although a mean volumetric productivity of 0.56 g L-1 h-1 was achieved, it was not possible to maintain this productivity, which collapsed to almost 0 g L-1 h-1. Therefore, two process adaptations were evaluated, a sequential batch strategy and a phosphate limitation alleviation strategy. The sequential batch set-up restored the mean volumetric productivity to 0.66 g L-1 h-1 for an additional 132 h but was again followed by a productivity decline. A similar result was obtained with the phosphate limitation alleviation strategy where a mean volumetric productivity of 0.54 g L-1 h-1 was reached, but a productivity decline was also observed. Whole genome variant analysis uncovered no evidence for genomic variations for up to 1306 h of retentostat cultivation. Untargeted metabolomics analysis identified 8-hydroxyguanosine, a biomarker for oxidative RNA damage, as a key metabolite correlating with high bolaform sophorolipid productivity. This study showcases the application of a retentostat to increase bolaform sophorolipid productivity and lays the basis of a multi-omics platform for in depth investigation of microbial biosurfactant production with S. bombicola.

Paediatric obesity: a systematic review and pathway mapping of metabolic alterations underlying early disease processes.

BACKGROUND: The alarming trend of paediatric obesity deserves our greatest awareness to hinder the early onset of metabolic complications impacting growth and functionality. Presently, insight into molecular mechanisms of childhood obesity and associated metabolic comorbidities is limited. This systematic review aimed at scrutinising what has been reported on putative metabolites distinctive for metabolic abnormalities manifesting at young age by searching three literature databases (Web of Science, Pubmed and EMBASE) during the last 6 years (January 2015-January 2021). Global metabolomic profiling of paediatric obesity was performed (multiple biological matrices: blood, urine, saliva and adipose tissue) to enable overarching pathway analysis and network mapping. Among 2792 screened Q1 articles, 40 met the eligibility criteria and were included to build a database on metabolite markers involved in the spectrum of childhood obesity. Differential alterations in multiple pathways linked to lipid, carbohydrate and amino acid metabolisms were observed. High levels of lactate, pyruvate, alanine and acetate marked a pronounced shift towards hypoxic conditions in children with obesity, and, together with distinct alterations in lipid metabolism, pointed towards dysbiosis and immunometabolism occurring early in life. Additionally, aberrant levels of several amino acids, most notably belonging to tryptophan metabolism including the kynurenine pathway and its relation to histidine, phenylalanine and purine metabolism were displayed. Moreover, branched-chain amino acids were linked to lipid, carbohydrate, amino acid and microbial metabolism, inferring a key role in obesity-associated insulin resistance. CONCLUSIONS: This systematic review revealed that the main metabolites at the crossroad of dysregulated metabolic pathways underlying childhood obesity could be tracked down to one central disturbance, i.e. impending insulin resistance for which reference values and standardised measures still are lacking. In essence, glycolytic metabolism was evinced as driving energy source, coupled to impaired Krebs cycle flux and ß-oxidation. Applying metabolomics enabled to retrieve distinct metabolite alterations in childhood obesity(-related insulin resistance) and associated pathways at early age and thus could provide a timely indication of risk by elucidating early-stage biomarkers as hallmarks of future metabolically unhealthy phenotypes.

Comprehensive polar metabolomics and lipidomics profiling discriminates the transformed from the non-transformed state in colon tissue and cell lines.

Colorectal cancer (CRC) is the fourth most lethal disease worldwide. Despite an urgent need for therapeutic advance, selective target identification in a preclinical phase is hampered by molecular and metabolic variations between cellular models. To foster optimal model selection from a translational perspective, we performed untargeted ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry-based polar metabolomics and lipidomics to non-transformed (CCD841-CON and FHC) and transformed (HCT116, HT29, Caco2, SW480 and SW948) colon cell lines as well as tissue samples from ten colorectal cancer patients. This unveiled metabolic signatures discriminating the transformed from the non-transformed state. Metabolites involved in glutaminolysis, tryptophan catabolism, pyrimidine, lipid and carnitine synthesis were elevated in transformed cells and cancerous tissue, whereas those involved in the glycerol-3-phosphate shuttle, urea cycle and redox reactions were lowered. The degree of glutaminolysis and lipid synthesis was specific to the colon cancer cell line at hand. Thus, our study exposed pathways that are specifically associated with the transformation state and revealed differences between colon cancer cell lines that should be considered when targeting cancer-associated pathways.

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.

Triangulation of microbial fingerprinting in anaerobic digestion reveals consistent fingerprinting profiles.

The anaerobic digestion microbiome has been puzzling us since the dawn of molecular methods for mixed microbial community analysis. Monitoring of the anaerobic digestion microbiome can either take place via a non-targeted holistic evaluation of the microbial community through fingerprinting or by targeted monitoring of selected taxa. Here, we compared four different microbial community fingerprinting methods, i.e., amplicon sequencing, metaproteomics, metabolomics and cytomics, in their ability to characterise the full-scale anaerobic digestion microbiome. Cytometric fingerprinting through cytomics reflects a, for anaerobic digestion, novel, single cell-based approach of direct microbial community fingerprinting by flow cytometry. Three different digester types, i.e., sludge digesters, digesters treating agro-industrial waste and dry anaerobic digesters, each reflected different operational parameters. The α-diversity analysis yielded inconsistent results, especially for richness, across the different methods. In contrast, ß-diversity analysis resulted in comparable profiles, even when translated into phyla or functions, with clear separation of the three digester types. In-depth analysis of each method's features i.e., operational taxonomic units, metaproteins, metabolites, and cytometric traits, yielded certain similar features, yet, also some clear differences between the different methods, which was related to the complexity of the anaerobic digestion process. In conclusion, cytometric fingerprinting through flow cytometry is a reliable, fast method for holistic monitoring of the anaerobic digestion microbiome, and the complementary identification of key features through other methods could give rise to a direct interpretation of anaerobic digestion process performance.

Sample Preparation Free Mass Spectrometry Using Laser-Assisted Rapid Evaporative Ionization Mass Spectrometry: Applications to Microbiology, Metabolic Biofluid Phenotyping, and Food Authenticity.

Mass spectrometry has established itself as a powerful tool in the chemical, biological, medical, environmental, and agricultural fields. However, experimental approaches and potential application areas have been limited by a traditional reliance on sample preparation, extraction, and chromatographic separation. Ambient ionization mass spectrometry methods have addressed this challenge but are still somewhat restricted in requirements for sample manipulation to make it suitable for analysis. These limitations are particularly restrictive in view of the move toward high-throughput and automated analytical workflows. To address this, we present what we consider to be the first automated sample-preparation-free mass spectrometry platform utilizing a carbon dioxide (CO2) laser for sample thermal desorption linked to the rapid evaporative ionization mass spectrometry (LA-REIMS) methodology. We show that the pulsatile operation of the CO2 laser is the primary factor in achieving high signal-to-noise ratios. We further show that the LA-REIMS automated platform is suited to the analysis of three diverse biological materials within different application areas. First, clinical microbiology isolates were classified to species level with an accuracy of 97.2%, the highest accuracy reported in current literature. Second, fecal samples from a type 2 diabetes mellitus cohort were analyzed with LA-REIMS, which allowed tentative identification of biomarkers which are potentially associated with disease pathogenesis and a disease classification accuracy of 94%. Finally, we showed the ability of the LA-REIMS system to detect instances of adulteration of cooking oil and determine the geographical area of production of three protected olive oil products with 100% classification accuracy.

The Bee Hemolymph Metabolome: A Window into the Impact of Viruses on Bumble Bees.

State-of-the-art virus detection technology has advanced a lot, yet technology to evaluate the impacts of viruses on bee physiology and health is basically lacking. However, such technology is sorely needed to understand how multi-host viruses can impact the composition of the bee community. Here, we evaluated the potential of hemolymph metabolites as biomarkers to identify the viral infection status in bees. A metabolomics strategy based on ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry was implemented. First, we constructed a predictive model for standardized bumble bees, in which non-infected bees were metabolically differentiated from an overt Israeli acute paralysis virus (IAPV) infection (R2Y = 0.993; Q2 = 0.906), as well as a covert slow bee paralysis virus (SBPV) infection (R2Y = 0.999; Q2 = 0.875). Second, two sets of potential biomarkers were identified, being descriptors for the metabolomic changes in the bee's hemolymph following viral infection. Third, the biomarker sets were evaluated in a new dataset only containing wild bees and successfully discriminated virus infection versus non-virus infection with an AUC of 0.985. We concluded that screening hemolymph metabolite markers can underpin physiological changes linked to virus infection dynamics, opening promising avenues to identify, monitor, and predict the effects of virus infection in a bee community within a specific environment.

Metabolic Fingerprinting of Feces from Calves, Subjected to Gram-Negative Bacterial Endotoxin.

Gram-negative bacteria have a well-known impact on the disease state of neonatal calves and their mortality. This study was the first to implement untargeted metabolomics on calves' fecal samples to unravel the effect of Gram-negative bacterial endotoxin lipopolysaccharide (LPS). In this context, calves were challenged with LPS and administered with fish oil, nanocurcumin, or dexamethasone to evaluate treatment effects. Ultra-high-performance liquid-chromatography high-resolution mass spectrometry (UHPLC-HRMS) was employed to map fecal metabolic fingerprints from the various groups before and after LPS challenge. Based on the generated fingerprints, including 9650 unique feature ions, significant separation according to LPS group was achieved through orthogonal partial least squares discriminant analysis (Q2 of 0.57 and p-value of 0.022), which allowed the selection of 37 metabolites as bacterial endotoxin markers. Tentative identification of these markers suggested that the majority belonged to the subclass of the carboxylic acid derivatives-amino acids, peptides, and analogs-and fatty amides, with these subclasses playing a role in the metabolism of steroids, histidine, glutamate, and folate. Biological interpretations supported the revealed markers' potential to aid in disease diagnosis, whereas beneficial effects were observed following dexamethasone, fish oil, and nanocurcumin treatment.

Untargeted Metabolomics Reveals Elevated L-Carnitine Metabolism in Pig and Rat Colon Tissue Following Red Versus White Meat Intake.

SCOPE: The consumption of red and processed meat, and not white meat, associates with the development of various Western diseases such as colorectal cancer and type 2 diabetes. This work aims at unraveling novel meat-associated mechanisms that are involved in disease development. METHODS AND RESULTS: A non-hypothesis driven strategy of untargeted metabolomics is applied to assess colon tissue from rats (fed a high dose of beef vs. white meat) and from pigs (fed red/processed meat vs. white meat), receiving a realistic human background diet. An increased carnitine metabolism is observed, which is reflected by higher levels of acylcarnitines and 3-dehydroxycarnitine (rats and pigs) and trimethylamine-N-oxide (rats). While 3-dehydroxycarnitine is higher in HT29 cells, incubated with colonic beef digests, acylcarnitine levels are reduced. This suggests an altered response from colon cancer cell line towards meat-induced oxidative stress. Moreover, metabolic differences between rat and pigs are observed in N-glycolylneuraminic acid incorporation, prostaglandin, and fatty acid synthesis. CONCLUSION: This study demonstrates elevated (acyl)carnitine metabolism in colon tissue of animals that follow a red meat-based diet, providing mechanistic insights that may aid in explaining the nutritional-physiological correlation between red/processed meat and Western diseases.

Metabolomics Reveal Induction of ROS Production and Glycosylation Events in Wheat Upon Exposure to the Green Leaf Volatile Z-3-Hexenyl Acetate.

The activation and priming of plant defense upon perception of green leaf volatiles (GLVs) have often been reported. However, information as to which metabolic pathways in plants are affected by GLVs remains elusive. We report the production of reactive oxygen species in the tip of young wheat leaves followed by activation of antioxidant-related enzyme activity. In this study, we aimed to uncover metabolic signatures upon exposure to the GLV Z-3-hexenyl acetate (Z-3-HAC). By using an untargeted metabolomics approach, we observed changes in the phenylpropanoid pathways which yield metabolites that are involved in many anti-oxidative processes. Furthermore, exposure to GLV, followed by infection with Fusarium graminearum (Fg), induced significantly greater changes in the phenylpropanoid pathway compared to a sole Z-3-HAC treatment. Fragmentation of a selection of metabolites, which are significantly more upregulated in the Z-3-HAC + Fg treatment, showed D-glucose to be present as a substructure. This suggests that Z-3-HAC induces early glycosylation processes in plants. Additionally, we identified the presence of hexenyl diglycosides, which indicates that aerial Z-3-HAC is metabolized in the leaves by glycosyltransferases. Together these data indicate that GLV Z-3-HAC is taken up by leaves and incites oxidative stress. This subsequently results in the modulation of the phenylpropanoid pathway and an induction of glycosylation processes.

Rapid LA-REIMS and comprehensive UHPLC-HRMS for metabolic phenotyping of feces.

Ambient ionization-based techniques hold great potential for rapid point-of-care applicable metabolic fingerprinting of tissue and fluids. Hereby, feces represents a unique biospecimen as it integrates the complex interactions between the diet, gut microbiome and host, and is therefore ideally suited to study the involvement of the diet-gut microbiome axis in metabolic diseases and their treatments at a molecular level. We present a new method for rapid (<10 s) metabolic fingerprinting of feces, i.e. laser-assisted rapid evaporative ionization mass spectrometry (LA-REIMS) with an Nd:YAG laser (2940 nm) and quadrupole Time-of-Flight mass spectrometer as main components. The LA-REIMS method was implemented on mimicked crude feces samples from individuals that were assigned a state of type 2 diabetes or euglycaemia. Based on the generated fingerprints, enclosing 4923 feature ions, significant segregation according to disease classification was achieved through orthogonal partial least squares discriminant analysis (Q2(Y) of 0.734 and p-value of 1.93e-17) and endorsed by a general classification accuracy of 90.5%. A comparison between the discriminative performance of the novel LA-REIMS and our established ultra-high performance liquid-chromatography high-resolution MS (UHPLC-HRMS) metabolomics and lipidomics methodologies for fingerprinting of stool was performed. Based on the supervised modelling results upon UHPLC-HRMS (Q2(Y) ≥ 0.655 and p-value ≤ 4.11 e-5), equivalent or better discriminative performance of LA-REIMS fingerprinting was concluded. Eventually, comprehensive UHPLC-HRMS was employed to assess metabolic alterations as observed for the defined classes, whereby metformin treatment of the type 2 diabetes patients was considered a relevant study factor to acquire new mechanistic insights. More specifically, ten metabolization products of metformin were identified, with (hydroxylated) triazepinone and metformin-cholesterol reported for the first time in vivo.In conclusion, LA-REIMS was established as an expedient strategy for rapid metabolic fingerprinting of feces, whereby potential implementations may relate, but are not limited to differential diagnosis and treatment efficacy evaluation of metabolic diseases. Yet, LC-HRMS remains essential for in-depth biological interpretation.

Untargeted Metabolomics to Reveal Red versus White Meat-Associated Gut Metabolites in a Prudent and Western Dietary Context.

SCOPE: To improve understanding of the epidemiological link between red and processed meat consumption and chronic diseases, more insight into the formation of metabolites during meat digestion is warranted. METHODS AND RESULTS: Untargeted mass-spectrometry-based metabolomics is applied to explore the impact of red and processed meat consumption (compared to chicken), combined with a prudent or Western dietary pattern. A pig feeding study (n = 32), as a sentinel for humans, is conducted in a 2 × 2 factorial design for 4 weeks. The luminal content of the small intestine and colon are collected to determine their metabolic fingerprints. Seventy-six metabolites (38 in the small intestine, 32 in the colon, and 6 in both intestinal compartments) contributing to the distinct gut metabolic profiles of pigs fed either chicken or red and processed meat are (tentatively) identified. Consumption of red and processed meat results in higher levels of short- and medium-chain acylcarnitines and 3-dehydroxycarnitine, irrespective of dietary context, whereas long-chain acylcarnitines and monoacylglycerols are associated with the red and processed Western diet. CONCLUSION: The identification of red and processed meat-associated gut metabolites in this study contributes to the understanding of meat digestion in a complex but controlled dietary context and its potential health effects.

Metabolomic Analysis of Cricket paralysisvirus Infection in Drosophila S2 Cells Reveals Divergent Effects on Central Carbon Metabolism as Compared with Silkworm Bm5 Cells.

High-throughput approaches have opened new opportunities for understanding biological processes such as persistent virus infections, which are widespread. However, the potential of persistent infections to develop towards pathogenesis remains to be investigated, particularly with respect to the role of host metabolism. To explore the interactions between cellular metabolism and persistent/pathogenic virus infection, we performed untargeted and targeted metabolomic analysis to examine the effects of Cricket paralysis virus (CrPV, Dicistroviridae) in persistently infected silkworm Bm5 cells and acutely infected Drosophila S2 cells. Our previous study (Viruses 2019, 11, 861) established that both glucose and glutamine levels significantly increased during the persistent period of CrPV infection of Bm5 cells, while they decreased steeply during the pathogenic stages. Strikingly, in this study, an almost opposite pattern in change of metabolites was observed during different stages of acute infection of S2 cells. More specifically, a significant decrease in amino acids and carbohydrates was observed prior to pathogenesis, while their abundance significantly increased again during pathogenesis. Our study illustrates the occurrence of diametrically opposite changes in central carbon mechanisms during CrPV infection of S2 and Bm5 cells that is possibly related to the type of infection (acute or persistent) that is triggered by the virus.

Validated Ultra-High-Performance Liquid Chromatography Hybrid High-Resolution Mass Spectrometry and Laser-Assisted Rapid Evaporative Ionization Mass Spectrometry for Salivary Metabolomics.

Whereas urine and blood are typically targeted in clinical research, saliva represents an interesting alternative because its intrinsic metabolome is chemically diverse and reflective for various biological processes. Moreover, saliva collection is easy and noninvasive, which is especially valuable for cohorts in which sample collection is challenging, for example, infants and children. With this rationale, we established a validated ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS) method for salivary metabolic profiling and fingerprinting. Hereby, 450 µL of saliva was centrifuged and passed over a 0.45-µm polyamide membrane filter, after which the extract was subjected to chromatographic analysis (HSS T3 column) and Q-Exactive Orbitrap-MS. For the majority of the profiled metabolites, good linearity (R2 ≥ 0.99) and precision (coefficient of variance ≤ 15%) was achieved. The fingerprinting performance was evaluated based on the complete metabolome (11 385 components), whereby 76.8% was found compliant with the criteria for precision (coefficient of variance ≤ 30%) and 82.7% with linearity (R2 ≥ 0.99). In addition, the method was proven fit-for-purpose for a cohort of 140 adolescents (6-16 years, stratified according to weight), yielding relevant profiles (45 obesity-related metabolites) and discriminative fingerprints (Q2 of 0.784 for supervised discriminant analysis). Alternatively, laser-assisted rapid evaporative ionization mass spectrometry (LA-REIMS) was established for rapid fingerprinting of saliva, thereby using a Nd:YAG laser and Xevo G2-XS QToF-MS. With an acquisition time of 0.5 min per sample, LA-REIMS offers unique opportunities for point-of-care applications. In conclusion, this work presents a platform of UHPLC-HRMS and LA-REIMS, complementing each other to perform salivary metabolomics.

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.

A Metabolomics Approach to Unravel Cricket Paralysis Virus Infection in Silkworm Bm5 Cells.

How a host metabolism responds to infection with insect viruses and how it relates to pathogenesis, is little investigated. Our previous study observed that Cricket paralysis virus (CrPV, Dicistroviridae) causes short term persistence in silkworm Bm5 cells before proceeding to acute infection. In this study, a metabolomics approach based on high resolution mass spectrometry was applied to investigate how a host metabolism is altered during the course of CrPV infection in Bm5 cells and which changes are characteristic for the transition from persistence to pathogenicity. We observed that CrPV infection led to significant and stage-specific metabolic changes in Bm5 cells. Differential metabolites abundance and pathway analysis further identified specific metabolic features at different stages in the viral life cycle. Notably, both glucose and glutamine levels significantly increased during CrPV persistent infection followed by a steep decrease during the pathogenic stages, suggesting that the central carbon metabolism was significantly modified during CrPV infection in Bm5 cells. In addition, dynamic changes in levels of polyamines were detected. Taken together, this study characterized for the first time the metabolic dynamics of CrPV infection in insect cells, proposing a central role for the regulation of both amino acid and carbohydrate metabolism during the period of persistent infection of CrPV in Bm5 cells.

Metabolomics-based biomarker discovery for bee health monitoring: A proof of concept study concerning nutritional stress in Bombus terrestris.

Bee pollinators are exposed to multiple natural and anthropogenic stressors. Understanding the effects of a single stressor in the complex environmental context of antagonistic/synergistic interactions is critical to pollinator monitoring and may serve as early warning system before a pollination crisis. This study aimed to methodically improve the diagnosis of bee stressors using a simultaneous untargeted and targeted metabolomics-based approach. Analysis of 84 Bombus terrestris hemolymph samples found 8 metabolites retained as potential biomarkers that showed excellent discrimination for nutritional stress. In parallel, 8 significantly altered metabolites, as revealed by targeted profiling, were also assigned as candidate biomarkers. Furthermore, machine learning algorithms were applied to the above-described two biomarker sets, whereby the untargeted eight components showed the best classification performance with sensitivity and specificity up to 99% and 100%, respectively. Based on pathway and biochemistry analysis, we propose that gluconeogenesis contributed significantly to blood sugar stability in bumblebees maintained on a low carbohydrate diet. Taken together, this study demonstrates that metabolomics-based biomarker discovery holds promising potential for improving bee health monitoring and to identify stressor related to energy intake and other environmental stressors.

Validated comprehensive metabolomics and lipidomics analysis of colon tissue and cell lines.

Current untargeted approaches for metabolic fingerprinting of colon tissue and cell lines lack validation of reproducibility and/or focus on a selection of metabolites as opposed to the entire metabolome. Yet, both are critical to ensure reliable results and pursue a fully holistic analysis. Therefore, we have optimized and validated a platform for analyzing the polar metabolome and lipidome of colon-derived cell and tissue samples based on a consecutive extraction of polar and apolar components. Peak areas of selected targeted analytes and the number of untargeted components were assessed. Analysis was performed using ultra-high performance liquid-chromatography (UHPLC) coupled to hybrid quadrupole-Orbitrap high-resolution mass spectrometry (HRMS). This resulted in an optimized extraction protocol using 50% methanol/ultrapure water to obtain the polar fraction followed by a dichloromethane-based lipid extraction. Using this comprehensive approach, we have detected more than 15,000 components with CV < 30% in internal quality control (IQC) samples and were able to discriminate the non-transformed (NT) and transformed (T) state in human colon tissue and cell lines based on validated OPLS-DA models (R2Y > 0.719 and Q2 > 0.674). To conclude, our validated polar metabolomics and lipidomics fingerprinting approach could be of great value to reveal gastrointestinal disease-associated biomarkers and mechanisms.