Assessing the adaptive role of cannabidiol (CBD) in Cannabis sativa defense against cannabis aphids.

Cannabis sativa is known for having unique specialized or secondary metabolites, cannabinoids that are derived from an extension of the terpene pathway in the Cannabis lineage and includes more than 100 other similar metabolites. Despite the assumption that cannabinoids evolved as novel herbivory defense adaptations, there is limited research addressing the role of cannabinoids in C. sativa responses to insect herbivores. Here we investigated the role of cannabidiol (CBD), the predominant cannabinoid in hemp, in plant defense against cannabis aphid (Phorodon cannabis), one of the most damaging pests of hemp. We hypothesize that insect feeding may induce changes in cannabinoids as an adaptive strategy for defense. We found that mean fecundity, net reproductive rate (R0) and adult longevity of cannabis aphids was reduced on the high cannabinoid cultivar compared to the low- cannabinoid cultivar in whole plant assays. In contrast, supplementation of CBD in artificial feeding assays increased aphid fecundity from day 1 to day 3. Additionally, aphid feeding did not impact cannabinoid levels in leaf tissues with the exception of Δ9-tetrahydrocannabinol (THC). This suggests that other cannabinoids and/or metabolites such as terpenes are causing the observed decrease in aphid performance in the whole plant assays. In addition to cannabinoids, C. sativa also possesses a range of defense mechanisms via phytohormone signaling pathways that are well described in other plant species. Indeed, cannabis aphid feeding significantly increased levels of the major phytohormones, salicylic acid, jasmonic acid, and abscisic acid, which are known to be involved in plant defense responses against aphid species. These results highlight the interplay between cannabinoid synthesis and phytohormone pathways and necessitate further investigation into this complex interaction.

Genomic prediction of seed nutritional traits in biparental families of oat (Avena sativa).

Selection for more nutritious crop plants is an important goal of plant breeding to improve food quality and contribute to human health outcomes. While there are efforts to integrate genomic prediction to accelerate breeding progress, an ongoing challenge is identifying strategies to improve accuracy when predicting within biparental populations in breeding programs. We tested multiple genomic prediction methods for 12 seed fatty acid content traits in oat (Avena sativa L.), as unsaturated fatty acids are a key nutritional trait in oat. Using two well-characterized oat germplasm panels and other biparental families as training populations, we predicted family mean and individual values within families. Genomic prediction of family mean exceeded a mean accuracy of 0.40 and 0.80 using an unrelated and related germplasm panel, respectively, where the related germplasm panel outperformed prediction based on phenotypic means (0.54). Within family prediction accuracy was more variable: training on the related germplasm had higher accuracy than the unrelated panel (0.14-0.16 and 0.05-0.07, respectively), but variability between families was not easily predicted by parent relatedness, segregation of a locus detected by a genome-wide association study in the panel, or other characteristics. When using other families as training populations, prediction accuracies were comparable to the related germplasm panel (0.11-0.23), and families that had half-sib families in the training set had higher prediction accuracy than those that did not. Overall, this work provides an example of genomic prediction of family means and within biparental families for an important nutritional trait and suggests that using related germplasm panels as training populations can be effective.

Nontargeted and Targeted Metabolomics Identifies Dietary Exposure Biomarkers for Navy Bean and Rice Bran Consumption in Children and Adults.

Dietary exposure biomarkers are needed for advancing knowledge on healthy foods. This study examined biomarkers for navy beans and rice bran in children and adults. Plasma, urine, stool, and study foods from dietary intervention studies were analyzed by metabolomics. A total of 38 children and 49 adults were assessed after consuming navy beans and/or rice bran for 2-, 4-, 6-, or 12 weeks. From the 138-175 metabolites modulated by diet, 11 were targeted for quantification. Trigonelline and pipecolate concentrations increased in children and adult plasma after 4 weeks compared to baseline. Increased xanthurenate (46%) was observed in children plasma after rice bran intake for 4 weeks. Study foods with navy beans had higher S-methylcysteine compared to control and supported the increased urine S-methylcysteine sulfoxide. Nontargeted metabolomics was moderately effective to identify target molecules as candidate biomarkers. Study limitations include interindividual metabolite variations before diet intervention. Validation is warranted using cross-over designs and larger sample sizes.

Quantitative analysis of short-chain fatty acids in human plasma and serum by GC-MS.

Short-chain fatty acids (SCFAs) are volatile fatty acids produced by gut microbial fermentation of dietary nondigestible carbohydrates. Acetate, propionate, and butyrate SCFA measures are important to clinical and nutritional studies for their established roles in promoting healthy immune and gut function. Additionally, circulating SCFAs may influence the metabolism and allied function of additional tissues and organs. The accurate quantification of SCFAs in plasma/serum is critical to understanding the biological role of SCFAs. The low concentrations of circulating SCFAs and their volatile nature present challenges for quantitative analysis. Herein, we report a sensitive method for SCFA quantification via extraction with methyl tert-butyl ether after plasma/serum acidification. The organic extract of SCFAs is injected directly with separation and detection using a polar GC column coupled to mass spectrometry. The solvent-to-sample ratio, plasma volume, and amount of HCl needed for SCFA protonation were optimized. Method validation shows good within-day and inter-day repeatability. The limit of detection was 0.3-0.6 µg/mL for acetate and 0.03-0.12 µg/mL for propionate and butyrate. Successful application of this method on clinical plasma and serum samples was demonstrated in six datasets. By simplifying the sample preparation procedure, the present method reduces the risk of contamination, lowers the cost of analysis, increases throughput, and offers the potential for automated sample preparation.

Multi-omics prediction of oat agronomic and seed nutritional traits across environments and in distantly related populations.

KEY MESSAGE: Integration of multi-omics data improved prediction accuracies of oat agronomic and seed nutritional traits in multi-environment trials and distantly related populations in addition to the single-environment prediction. Multi-omics prediction has been shown to be superior to genomic prediction with genome-wide DNA-based genetic markers (G) for predicting phenotypes. However, most of the existing studies were based on historical datasets from one environment; therefore, they were unable to evaluate the efficiency of multi-omics prediction in multi-environment trials and distantly related populations. To fill those gaps, we designed a systematic experiment to collect omics data and evaluate 17 traits in two oat breeding populations planted in single and multiple environments. In the single-environment trial, transcriptomic BLUP (T), metabolomic BLUP (M), G + T, G + M, and G + T + M models showed greater prediction accuracy than GBLUP for 5, 10, 11, 17, and 17 traits, respectively, and metabolites generally performed better than transcripts when combined with SNPs. In the multi-environment trial, multi-trait models with omics data outperformed both counterpart multi-trait GBLUP models and single-environment omics models, and the highest prediction accuracy was achieved when modeling genetic covariance as an unstructured covariance model. We also demonstrated that omics data can be used to prioritize loci from one population with omics data to improve genomic prediction in a distantly related population using a two-kernel linear model that accommodated both likely casual loci with large-effect and loci that explain little or no phenotypic variance. We propose that the two-kernel linear model is superior to most genomic prediction models that assume each variant is equally likely to affect the trait and can be used to improve prediction accuracy for any trait with prior knowledge of genetic architecture.

The Detection of Vancomycin in Sweat: A Next-Generation Digital Surrogate Marker for Antibiotic Tissue Penetration: A Pilot Study.

BACKGROUND: Assuring adequate antibiotic tissue concentrations at the point of infection, especially in skin and soft tissue infections, is pivotal for an effective treatment and cure. Despite the global issue, a reliable AB monitoring test is missing. Inadequate antibiotic treatment leads to the development of antimicrobial resistances and toxic side effects. ß-lactam antibiotics were already detected in sweat of patients treated with the respective antibiotics intravenously before. With the emergence of smartphone-based biosensors to analyse sweat on the spot of need, next-generation molecular digital biomarkers will be increasingly available for a non-invasive pharmacotherapy monitoring. OBJECTIVE: Here, we investigated if the glycopeptide antibiotic vancomycin is detectable in sweat samples of in-patients treated with intravenous vancomycin. METHODS: Eccrine sweat samples were collected using the Macroduct Sweat Collector®. Along every sweat sample, a blood sample was taken. Bio-fluid analysis was performed by Ultra-high Pressure Liquid Chromatograph-Tandem Quadrupole Mass Spectrometry coupled with tandem mass spectrometry. RESULTS: A total of 5 patients were included. Results demonstrate that vancomycin was detected in 5 out of 5 sweat samples. Specifically, vancomycin concentrations ranged from 0.011 to 0.118 mg/L in sweat and from 4.7 to 8.5 mg/L in blood. CONCLUSION: Our results serve as proof-of-concept that vancomycin is detectable in eccrine sweat and may serve as a surrogate marker for antibiotic tissue penetration. A targeted vancomycin treatment is crucial in patients with repetitive need for antibiotics and a variable antibiotic distribution such as in peripheral artery disease to optimize treatment effectiveness. If combined with on-skin smartphone-based biosensors and smartphone applications, the detection of antibiotic concentrations in sweat might enable a first digital, on-spot, lab-independent and non-invasive therapeutic drug monitoring in skin and soft tissue infections.

Biological variation of major gut-derived uremic toxins in the serum of healthy adult cats.

BACKGROUND: Biological variation of serum indoxyl sulfate (IS), p-cresol sulfate (pCS), and trimethylamine-n-oxide (TMAO) concentrations in cats is unknown. OBJECTIVES: To determine short- and medium-term biological variation, index of individuality (II), and reference change values for serum IS, pCS, and TMAO concentrations in healthy adult cats. To determine the effect of feeding on serum concentrations. ANIMALS: Twelve healthy adult cats. METHODS: Prospective, cohort study. Seven serum samples over a 12-hour period (short-term) and 5 serum samples over a 19-day period (medium-term) were collected. Serum concentrations of total IS, pCS, and TMAO were measured every 2 hours in a 12-hour period (hours 0-12) after a meal in 9 cats and compared to concentrations in a nonfed state. RESULTS: For IS, the II was high using short-term (1.96) and low using medium-term (0.65) biological variation estimates. Individuality was intermediate for pCS (short-term, 0.98; medium-term, 1.17) and TMAO (short-term, 1.47; medium-term, 0.83). Serum IS, pCS, and TMAO concentrations were significantly lower in a fed state compared to a nonfed state at hours 4, 6, 8, and 12; at hours 4 and 6; and at hours 2, 4, 6, 8, 10, 12, respectively. CONCLUSION AND CLINICAL IMPORTANCE: Population-based reference intervals with reference to the subject-based interval can be used to monitor serum pCS and TMAO concentrations. For IS, a subject-based and a population-based reference interval is best for short-term and medium-term monitoring, respectively. To compare serial measurements, it would be prudent to collect samples at the same time of day and consistently in either a fed or nonfed state.

Application of Predicted Collisional Cross Section to Metabolome Databases to Probabilistically Describe the Current and Future Ion Mobility Mass Spectrometry.

Metabolomics is a powerful phenotyping platform with potential for high-throughput analyses. The primary technology for metabolite profiling is mass spectrometry. In recent years, the coupling of mass spectrometry with ion mobility spectrometry (IMS) has offered the promise of faster analysis time and greater resolving power. Our understanding of the potential impact of IMS on the field of metabolomics is limited by availability of comprehensive experimental data. In this analysis, we use a probabilistic approach to enumerate the strengths and limitations, the present and future, of this technology. This is accomplished through use of "model" metabolomes, predicted physicochemical properties, and probabilistic descriptions of resolving power. This analysis advances our understanding of the importance of orthogonality in resolving (separation) dimensions, describes the impact of the metabolome composition on resolution demands, and offers a system resolution landscape that may serve to guide practitioners in the coming years.

Fatty acids present in commercial albumin preparations differentially affect development of murine embryos before and during implantation.

OBJECTIVE: To characterize fatty acid (FA) profile of commercially available albumin products and determine their effect on embryonic development. DESIGN: Research study. SETTING: Private research facility. ANIMAL(S): Outbred mice aged 4-8 weeks. INTERVENTION(S): Gas chromatography-mass spectrometry was used to quantify the FA content of 15 commercial albumins. Embryos were produced in media containing different albumin products, with or without carnitine or exogenous FA supplementation, to determine their effect on embryo development in vitro. MAIN OUTCOME MEASURE(S): Total micrograms of FA per milligram of albumin for the 15 albumin products, blastocyst development, cell number, allocation to the trophectoderm (TE) or inner cell mass (ICM), and evaluation of morphology during implantation. RESULT(S): The albumin products contained 0.07-16.77 µg total FA/mg albumin. Compared to media with with >1.4 µg FA/mg albumin, media with <0.5 µg FA/mg albumin supported improved blastocyst development, and addition of carnitine mitigated this difference. Addition of palmitoleic acid or oleic acid individually did not improve blastocyst development and decreased ICM:TE ratio. However, in the presence of carnitine, there was improved blastocyst development and maintenance of the ICM:TE ratio. Embryos cultured in Vitrolife human serum albumin with supplementation of carnitine, palmitoleic acid, and oleic acid were more likely to develop cells positive for POU5F1 in an extended embryo culture than embryos cultured in Origio serum protein substitute. CONCLUSION(S): Commercial albumin products contain FAs, which vary in abundance. These FAs have different effects on embryo development and quality before and during the implantation stage. Several of these albumin preparations are routinely used for human-assisted reproductive technologies; therefore, serious consideration is warranted when selecting a product for clinical use.

Metabolites from Wild Potato Inhibit Virulence Factors of the Soft Rot and Blackleg Pathogen Pectobacterium brasiliense.

Potato (Solanum tuberosum L.) is the primary vegetable crop consumed worldwide and is largely affected by bacterial pathogens that can cause soft rot and blackleg disease. Recently, resistance to these diseases has been identified in the wild potato S. chacoense, and the mechanism of resistance is unknown. Here, it was hypothesized that S. chacoense stems or tubers have unique chemistry that confers resistance to the pathogen Pectobacterium brasiliense through bactericidal, bacteriostatic, or antivirulence activity. Stem and tuber metabolite extracts were collected from S. chacoense and tested for effects on Pectobacterium bacterial multiplication rates, and activity and expression of known exoenzymes and virulence genes using S. tuberosum extracts as a comparative control. Comparatively, the S. chacoense extracts did not affect bacterial multiplication rate; however, they did reduce pectinase, cellulase, and protease activities. The chemical extracts were profiled using a bioassay-guided fractionation, and a nontargeted metabolomics comparison of S. chacoense and S. tuberosum stems and tubers was performed. The data showed that selected alkaloids, phenolic amines, phenols, amines, and peptides are integrative chemical sources of resistance against the bacteria.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Effects of time and temperature during melanging on the volatile profile of dark chocolate.

Chocolate made from small-batch production is known for distinct sensory properties that differentiate its products from large-scale production. Specifically, small-batch processing includes a melanging step, a chocolate refining (a process involving time and temperature to refine texture and flavor) process that occurs in a stone wet-grinder. Chocolatiers understand that melanging is essential to flavor and overall quality, however the influence of melanging on the aroma chemistry of the finished chocolate is anecdotal and largely uncharacterized. Here, we evaluated the effects of time and temperature of melanging on the volatile chemistry of the finished chocolate. Specifically, chocolate aroma was profiled using HS/SPME-GC-MS for three different time and temperature combinations. A total of 88 compounds were annotated by mass spectrometry and included a diverse set of chemical classes such as pyrazines, aldehydes, terpenes, alcohols, esters, and ketones. Analysis of variance (ANOVA), principal component analysis (PCA), and partial least squares analysis (PLS) revealed that the overall aroma profile was influenced by the type of melanging, and time had a greater effect than temperature. Example compounds affected by time include 2-methylpropanal, dimethyl sulfide, and benzaldehyde. Particle size was also measured for each sample. Majority particle size was found to be below 25 microns generally at all time points beyond 8 h. Analysis showed significant p-values for the temperature variable for several compounds, but significant p-values for the time variable were apparent for a greater number of compounds. For compounds which showed dependency on both time and temperature, the p-value for the time variable was much smaller in most cases. Both PCA and OPLS analyses suggested the same trends. These data support that time is a critical factor in determining the aroma chemistry of chocolate and affects a diverse set of known flavor active compounds.

Quantitative Analysis of Ethyl Carbamate in Distillers Grains Co-products and Bovine Plasma by Gas Chromatography-Mass Spectrometry.

Ethyl carbamate (EC) is a fermentation byproduct in foods and beverages and classified as a Group 2A probable human carcinogen. Each year, greater than 40 million metric tons of fermentation co-products from the U.S. ethanol industry are fed to food animals. A gas chromatography-mass spectrometry assay was developed to quantify EC extracted from various distillers grains co-products with a limit of detection at 0.7 ng/g (on an as-fed basis). EC was detected in all the distillers grains co-products surveyed in this study. Corn condensed distillers solubles contained the highest concentration of EC, ranging from 1618 to 2956 ng/g. Concentrations of EC in other types of distillers grains co-products varied from 17 to 917 ng/g. Cattle fed distillers grains co-products that constituted 19-38% of the total feed (as-fed) were found to contain 2-3 ng/mL of EC in blood plasma. No EC was detected in blood plasma from grass-fed control cattle.

Metabolic compounds within the porcine uterine environment are unique to the type of conceptus present during the early stages of blastocyst elongation.

The objective of this study was to identify metabolites within the porcine uterine milieu during the early stages of blastocyst elongation. At Days 9, 10, or 11 of gestation, reproductive tracts of White cross-bred gilts (n = 38) were collected immediately following harvest and flushed with Roswell Park Memorial Institute-1640 medium. Conceptus morphologies were assessed from each pregnancy and corresponding uterine flushings were assigned to one of five treatment groups based on these morphologies: (a) uniform spherical (n = 8); (b) heterogeneous spherical and ovoid (n = 8); (c) uniform ovoid (n = 8); (d) heterogeneous ovoid and tubular (n = 8); and (e) uniform tubular (n = 6). Uterine flushings from these pregnancies were submitted for nontargeted profiling by gas chromatography-mass spectrometry (GC-MS) and ultra performance liquid chromatography (UPLC)-MS techniques. Unsupervised multivariate principal component analysis (PCA) was performed using pcaMethods and univariate analysis of variance was performed in R with false discovery rate (FDR) adjustment. PCA analysis of the GC-MS and UPLC-MS data identified 153 and 104 metabolites, respectively. After FDR adjustment of the GC-MS and UPLC-MS data, 38 and 59 metabolites, respectively, differed (p < .05) in uterine flushings from pregnancies across the five conceptus stages. Some metabolites were greater (p < .05) in abundance for uterine flushings containing earlier stage conceptuses (i.e., spherical), such as uric acid, tryptophan, and tyrosine. In contrast, some metabolites were greater (p < .05) in abundance for uterine flushings containing later stage conceptuses (i.e., tubular), such as creatinine, serine, and urea. These data illustrate several putative metabolites that change within the uterine milieu during early porcine blastocyst elongation.

White Kidney Bean (Phaseolus Vulgaris L.) Consumption Reduces Fat Accumulation in a Polygenic Mouse Model of Obesity.

Clinical studies indicate that eating common bean, Phaseolus vulgaris L., plays a role in body weight regulation but mechanisms have yet to be elucidated. Here, we investigated the anti-obesogenic activity of white kidney bean in a mouse model of dietary-induced obesity. Bean consumption reduced the accumulation of adipose tissue in male and female C57BL6 mice. The anti-obesogenic effect of white kidney bean was not due to alterations in energy intake, energy excreted in the feces, or feed efficiency ratio. While bean consumption increased the mass of the intestine, no marked differences were consistently observed in crypt height, mucin content of goblet cells, proliferation index or zone of proliferation. However, significantly higher concentrations of total bacteria and of Akkermansia muciniphila were detected in cecal content of bean-fed mice, and the ratio of Firmicutes to Bacteroidetes was reduced. Bile acid content was higher in the ileum of bean-fed mice, but transcript levels of farnesoid X receptor were not significantly affected. Whether changes in bile-acid-mediated cell signaling play a role in bean-related differences in fat accumulation and/or overall metabolic health requires further investigation.

Data Processing for GC-MS- and LC-MS-Based Untargeted Metabolomics.

Gas chromatography and liquid chromatography coupled to mass spectrometry are used extensively in untargeted metabolomics, which involves the profiling of small metabolites in biological samples. The complex raw dataset produced from untargeted metabolomics requires proper processing before it can be statistically analyzed and interpreted. This chapter describes a high-throughput data processing workflow routinely used in our laboratory, including feature detection and alignment, data reduction, and spectral-matching-based annotation. This semiautomated workflow uses vendor neutral data file formats and freely available data processing tools and therefore can be readily implemented on datasets acquired from instruments of different vendors.

Microalgae lipid characterization.

To meet the growing interest of utilizing microalgae biomass in the production of biofuels and nutraceutical and pharmaceutical lipids, we need suitable analytical methods and a comprehensive database for their lipid components. The objective of the present work was to demonstrate methodology and provide data on fatty acid composition, lipid class content and composition, characteristics of the unsaponifiables, and type of chlorophylls of five microalgae. Microalgae lipids were fractionated into TAG, FFA, and polar lipids using TLC, and the composition of fatty acids in total lipids and in each lipid class, hydrocarbons, and sterols were determined by GC-MS. Glyco- and phospholipids were profiled by LC/ESI-MS. Chlorophylls and their related metabolites were qualified by LC/APCI-MS. The melting and crystallization profiles of microalgae total lipids and their esters were analyzed by DSC to evaluate their potential biofuel applications. Significant differences and complexities of lipid composition among the algae tested were observed. The compositional information is valuable for strain selection, downstream biomass fractionation, and utilization.

Flow rate and duty cycle effects in lysis of Chlamydomonas reinhardtii using high-energy pulsed focused ultrasound.

To consider microalgae lipid biofuel as a viable energy source, it is a necessity to maximize algal cell lysis, lipid harvest, and thus biofuel production versus the energy used to lyse the cells. Previous techniques have been to use energy consumptive ultrasound waves in the 10-40 kHz range in a stationary exposure environment. This study evaluated the potential of using 1.1 MHz ultrasound pulses in a new flow through type chamber on Chlamydomonas reinhardtii as a model organism for cell breakage. The ultrasound was generated using a spherically focused transducer with a focal length of 6.34 cm and an active diameter of 6.36 cm driven by 20 cycle sine-wave tone bursts at varied pulse repetition frequencies. First, variations in flow rate were examined at a constant duty cycle of 3.6%. After assessing flow rates, the duty cycle was varied to further explore the dependence on the tone burst parameters. Cell lysis was assessed by quantifying protein and chlorophyll release into the supernatant as well as by lipid extractability. Appropriate flow rates with higher duty cycles led to statistically significant increases in cell lysis relative to controls and other exposure conditions.

Lysis of Chlamydomonas reinhardtii by high-intensity focused ultrasound as a function of exposure time.

Efficient lysis of microalgae for lipid extraction is an important concern when processing biofuels. Historically, ultrasound frequencies in the range of 10-40 kHz have been utilized for this task. However, greater efficiencies might be achievable if higher frequencies could be used. In our study, we evaluated the potential of using 1.1 MHz ultrasound to lyse microalgae for biofuel production while using Chlamydomonas reinhardtii as a model organism. The ultrasound was generated using a spherically focused transducer with a focal length of 6.34 cm and an active diameter of 6.36 cm driven by 20 cycle sine-wave tone bursts at a pulse repetition frequency of 2 kHz (3.6% duty cycle). The time-average acoustic power output was 26.2 W while the spatial-peak-pulse-average intensity (ISPPA) for each tone burst was 41 kW/cm(2). The peak compressional and rarefactional pressures at the focus were 102 and 17 MPa, respectively. The exposure time was varied for the different cases in the experiments from 5s to 9 min and cell lysis was assessed by quantifying the percentage of protein and chlorophyll release into the supernate as well as the lipid extractability. Free radical generation and lipid oxidation for the different ultrasound exposures were also determined. We found that there was a statistically significant increase in lipid extractability for all of the exposures compared to the control. The longer exposures also completely fragmented the cells releasing almost all of the protein and chlorophyll into the supernate. The cavitation activity did not significantly increase lipid oxidation while there was a minor trend of increased free radical production with increased ultrasound exposure.

Oxidative stability of soybean oil in oleosomes as affected by pH and iron.

The oxidative stability of oil in soybean oleosomes, isolated using the Enzyme-Assisted Aqueous Extraction Process (EAEP), was evaluated. The effects of ferric chloride, at two concentration levels (100 and 500 µM), on lipid oxidation, was examined under pH 2 and 7. The peroxide value (PV) and thiobarbituric acid-reactive substance (TBARS) value of oil, in oleosome suspensions stored at 60 °C, were measured over a 12 day period. The presence of ferric chloride significantly (P<0.05) affected the oxidative stability of oil in the isolated oleosome, as measured by the PV and TBARS. Greater lipid oxidation occurred under an acidic pH. In the pH 7 samples, the positively charged transition metals were strongly attracted to the negatively charged droplets. However, the low ζ-potential and the high creaming rate at this pH, may have limited the oxidation. Freezing, freeze-drying or heating of oleosomes have an insignificant impact on the oxidative stability of oil in isolated soybean oleosomes. Manufacturers should be cautious when adding oleosomes as ingredients in food systems containing transition metal ions.