Location: Methods and Application of Food Composition Laboratory
2020 Annual Report
Objectives
Objective 1. Utilize comprehensive, non-targeted methods for classifying foods and for identifying candidate compounds that can then be quantified by specific targeted methods to determine the variance of nutritionally important food components in the western diet. (NP 107, Problem Statement 2A).
Objective 2. Apply comprehensive non-targeted methods to identify, and apply specific targeted methods to quantify, nutritionally important compounds in food crops that may be impacted by genetics, environment, management, and processing (GxExMxP). (NP 107, Problem Statement 1A and NP 216, Component 5)
Objective 3. In collaboration with other laboratories, utilize metabolite fingerprinting, metabolomics, and lipidomics to: A) characterize the impact of genetics, environment (including geographical location) and management on the nutritional characteristics of dry beans and soybeans; and B) evaluate the impact of bovine diet and environment on the nutritional composition (with emphasis on lipids) of milk and dairy products. (NP 107, Problem Statement 1A and 2A and NP 216, Component 5)
Objective 4. Demonstrate that comprehensive non-targeted analysis of individual samples from selected national studies prior to compositing is a critical compliment to targeted data in the new USDA Food Composition Database. (NP 107, Problem Statement 2A)
Approach
New analytical technology will be adapted to the analysis of foods to help nutritionist, health practitioners, and the public to understand the link between agricultural systems, nutrition, and health. The food supply is changing rapidly with new genotypes from the farm and new processed foods in the marketplace. Every food consists of thousands of compounds, each with the potential to impact human health. Each must be identified, quantified, and added to a database. For a database to keep pace with the new foods, high throughput must be combined with even more detailed, comprehensive analyses. Rapid screening methods, based on metabolite fingerprinting, will allow classification of foods and determination of the relative variance associated with food production factors. Selected samples from each class will be subjected to metabolomic and lipidomic analysis. These methods will produce libraries of compounds that will allow metabolite fingerprinting methods to be used for rapid identification and quantification and will fill out nutrient databases. The combination of fingerprinting, metabolomic, and lipidomic methods will be used to analyze commodities and processed foods and to evaluate the nutritional qualities of crops and food products as a function of genetics, environment, management, and processing. This data is critical to establishing relationships between agricultural systems, nutrition, and Health. Ultimately, this data will be combined into a single database available to researchers and the public.
Progress Report
Identification of early biomarkers for predicting browning of fresh-cut lettuce using untargeted ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS) metabolomics. The shelf-life of fresh-cut lettuce is limited by browning which could lead to consumer rejection. Metabolite composition of lettuce could be affected by browning process. The purpose of this study was to identify maker compounds to predict lettuce browning, which could be utilized to evaluate the accessions better suited for industrial breeding program. Two batches of romaine lettuce including 46 and 36 accessions, respectively, with different browning susceptibilities after cutting were used for metabolomic study. Multivariate analysis such as principal component analysis (PCA) was performed to visualize group clustering, trends, or outliers among the observations. Ten metabolites were identified to be positively or negatively related to browning process. Among them, organic acid, caffeoylquinic acid, hydroxy fatty acid and cichorioside B were increased with browning development, while, lactucopicrin-15-oxalate, tri-4-hydroxyphenylacetyl glucoside and 15-deoxylactucin-8-sulfate were negatively correlated with browning. Additionally, two phenolic metabolites such as dicaffeoyltartaric acid and caffeoyltartaric acid were also identified as potential marker compounds,as they were negatively correlated with the browning developed (represented as hue angle values) before storage. The identified metabolites would be promising marker compounds for industrial breeding program in future.
Metabolomic profiling and comparison of major cinnamon species using UHPLC–HRMS. The metabolomic profiles of cinnamon samples obtained from the four major species of Cinnamomum (verum, burmannii, loureiroi, and cassia) were investigated by ultra-high-performance liquid chromatography – high-resolution mass spectrometry (UHPLC¬–HRMS). Thirty-six metabolites were tentatively characterized, belonging to various compound groups such as phenolic glycosides, flavan-3-ols, phenolic acids, terpenes, alkaloids, and aldehydes. Principal component analysis (PCA) and partial least squares - discriminant analysis (PLS-DA) on the HRMS data matrix resulted in a clear separation of the four cinnamon species. Coumarin, cinnamaldehyde, methoxycinnamaldehyde, cinnamoyl-methoxyphenyl acetate, proanthocyanidins, and other components varied among certain species. The results suggest a significant variation on the phytochemical compositions of different cinnamon species, which have a direct influence on cinnamon’s health benefit potentials.
Iridoid glycosides with Escherichia coli-glucuronidase inhibitory effect from baobab fruit pulp (Adansonia digitata): UHPLC-HRMSn guided isolation and biological evaluation. A. digitata L, also known as baobab, has received more attention globally due to its multipurpose and high nutritional values. Baobab fruit pulp has been approved as food ingredient in European and U.S. markets. In this study, four new iridoid glycosides (IGs 1-4) and six known analogues (5-10) During the search for new bioactive (IGs) were isolated from the aqueous EtOH extract of baobab fruit pulp under the guidance of UHPLC-HRMSn analysis. The isolated compounds were assayed for their Escherichia coli ß-glucuronidase (EcGUS) inhibitory activities in vitro. The results indicated that compound 5-10 were potent mixed-type inhibitors of EcGUS, with IC50 values in the range 20.7 to 33.7 µM. And molecular docking studies predicted their molecular determinants for EcGUS inhibition. This research highlighted the discovery and design of potent IG inhibitors against EcGUS, paving a new pathway for the development of the functional food.
Chemical analysis and classification of black pepper (Piper nigrum L.) using mass spectrometric methods and chemometrics. The current study applied gas chromatography mass spectrometry (GC-MS), liquid chromatography mass spectrometry (LC-MS), and thermal desorption direct analysis in real time mass spectrometry (DART-MS) methods to the analysis of black pepper (Piper nigrum L.) samples. Various compounds such as piperamides and terpenes were observed during the analysis. Partial least squares-discriminant analysis (PLS-DA) was used to classify black pepper samples based on their origins. Total ion mass spectrum (TMS) data profiles from GC-MS, LC-MS, and DART-MS methods were constructed and evaluated for the performance of classification. A cubic-root data transformation was tested in the data preprocessing and found to be effective for improving the classification rates. The average classification rates of PLS-DA models with GC-MS-cubic-root-TMS, LC-MS-cubic-root-TMS, and DART-MS-cubic-root-TMS data representations were 94.1±0.6%, 87.7±0.6%, and 97.0±0.3% respectively for 100-time bootstrapped-Latin-partition cross validation. Thermal desorption DART-MS has been demonstrated as a simple and high-throughput method for discrimination studies of food materials.
Investigation of GxExMxP parameters in lettuce lipids. We analyzed the lipid extracts of romaine (green-leaf) and lolla rossa (red-leaf) varieties of lettuce by high performance liquid chromatography (HPLC) with detection by triple-parallel mass spectrometry (LC1MS3). Data from APCI-MS were used for targeted analysis (quantification) of alpha- and beta-tocopherols to monitor how they change with cultivar, age, and light exposure. Data from APPI-MS have been used for targeted (% relative quantification) of galactolipids (GALs), triacylglycerols (TAGs), and diacylglycerols (DAGs). This work touched on aspects of genetics (green- versus red-leaf lettuce), environment (greenhouse grown versus controlled environment), and management (different light treatments) on the nutritional quality of lettuce. A manuscript was submitted to the Journal of Food Composition and Analysis, and received a score of Minor Revision. But due to the need for more thorough error treatment, and other reasons, the manuscript has been completely re-written with an emphasis on the new reports of lipid compositions of TAGs, DAGs, and GALs, with less emphasis on tocopherols. The revised manuscript will be re-submitted as soon as possible.
Method development for separation of bovine milk short-chain TAGs by 3D-LC (LC3MS4). NIST Standard Reference Material (SRM) 1849a is an Adult/Infant Formula that has been formulated to contain a similar composition of lipids as bovine milk, especially including short-chain TAG isomers. Therefore, NIST SRM 1849a has been chosen as a model analyte to validate the method for bovine milk analysis. We have made progress on the development of useful columns for 3D-LC. Using a short C30 column as one 2nd dimension, combined with a longer C30 column, we are pioneering the use of a newly developed category of chromatography, called “multi-cycle, multi-dimensional chromatography”. We used principles similar to “twin-column recycling chromatography” to subject the analyte to multiple modulation periods in 3D-LC, to greatly improve the separation of TAGs. This groundbreaking new approach is being proved and validated on NIST SRM 1849a samples. Unlike unfortified bovine milk, NIST SRM 1849a has fat-soluble vitamins, so it will allow us to validate the method for absolute quantification of FSVs, as well as triacylglycerols (TAGs), diacylglycerols (DAGs), and others. Columns and conditions have been selected and optimized, and we are ready to acquire the final data runs for publication. A manuscript describing the first application of 3D-LC, with two parallel second dimensions, will be prepared as soon as the data are acquired, after the end of the pandemic lockdown.
High resolution in gas chromatography has been modified to allow separation of milk fatty acids. Current gas chromatography (GC) methods are inadequate for the analysis of bovine milk, which has a very complex fatty acid (FA) composition containing many more FAs than previous samples. Improved resolution in GC separations is necessary to separate the large number of isomers present in milk lipid extracts. The GC with flame ionization detection (FID) used for quantitative analysis of FAs has been changed over from helium to hydrogen as the carrier gas to try to improve the separation. More importantly, the columns in the GC-FID and GC-MS systems have been changed from Omegawax 250 columns to SP2560 columns, which give better separations of previously unresolved isomers. The focus has been on better separation of conjugated linolenic acid (CLnA), or 18:3, isomers.
Analysis of dry beans from the Pulsed Crop Health Initiative (PCHI). Methods and Application of Food Composition Lab (MAFCL) was one of 5 collaborators awarded funding under the USDA PCHI. Dry beans of multiple varieties were grown at multiple sites in North Dakota and Washington state. More than 2000 samples were collected over the first e years and have been analyzed by near infrared (NIR) spectrometry and high resolution mass spectrometry (HRMS). NIR allowed differentiation of samples with respect to state and sites, with little difference between varieties. HRMS, or metabolomics, identified more than 50 chemical components that were prominent in the beans. The study is ongoing for a third year and will provide data critical to the selection of varieties best suited for locations and climates.
Accomplishments
1. Impact of elevated CO2 levels on the chemical composition of wheat (Triticum aestivum). It is well established that higher ambient CO2 levels result in reduced nitrogen levels and higher trace metal content in plants; however, there have been few analyses of other plant components. Two wheat genetic lines (with 6 percent and 41 percent yield at elevated CO2) were grown under ambient and free-air CO2 enrichment (FACE) conditions and were subjected to a comprehensive chemical analysis. Metabolite profiling identified 50 compounds; amino acids, saccharides, phenolic acids, flavonoids, and lipids and showed that the sugars and fats were different in the 2 lines and 2 CO2 levels. For both lines elevated CO2 reduced the protein levels. These results show changes in chemical composition of wheat grown under elevated CO2.
2. Composition of a cold-pressed blackberry seed flour extract. Blackberry seed flour was analyzed for its phytochemical composition and health-beneficial properties. ARS scientists in Beltsville, Maryland, identified thirteen components that, collectively, increased the total number of gut bacteria and shifted the abundance of specific bacterial phylum, family, or genus. In addition, the blackberry seed flour extract showed capacity for anti-inflammation and antiproliferation by suppressing LPS induced IL-1ß mRNA expressions in the cultured J774A.1 mouse macrophages and the proliferation of LNCaP prostate cancer cells. The results suggest potential health benefits and further utilization of blackberry seed flour as a functional food.
3. Quantification of cranberry proanthocyanidins. American cranberries (Vaccinium macrocarpon) contain primarily the active compound A-type proanthocyanidins (PACs), which have been shown to prevent urinary tract infection. Currently, an accurate quantification of cranberry PACs is still lacking. ARS scientists in Beltsville, Maryland, quantified the PACs by NP-HPLC using relative response factors that yielded higher values in 3 food products. This method provides a more accurate approach in determining cranberry PACs.
4. Effect of nighttime UV-C irradiation of strawberry plants on phenolics content of the fruit. The new approach of using UV-C irradiation followed by a specific dark period to control plant diseases has the potential to become a mainstream treatment in the production of strawberries and other fruits and vegetables. ARS scientists in Beltsville, Maryland, studied the effects of this treatment on fruit quality. Results indicate that the content of anthocyanins, glucosides and glucuronides of quercetin and kaempferol, catechin, pelargonidin rutinoside, and ellagic acid was not affected by UV-C treatment.
5. Variations in the composition of wild and cultivated soybeans. Soybeans are an important food source for plant-based proteins, oil, and micronutrients. There has been significant interest in investigating the chemical variation of wild and cultivated soybeans to develop new value-added varieties with improved quality traits through conventional and molecular breeding programs. ARS scientists in Beltsville, Maryland, analyzed 14 wild and cultivated soybeans grown in five countries and showed that the soluble sugars and total fat differed. Lower oil levels were found in wild soybeans and that there is a positive relationship between oil and soluble sugars. These results are important to both classical and natural breeding programs for the development of new, value-added soybeans with improved nutritional quality.
6. Advances in the field of two dimensional chromatography. Cow’s milk contains an extremely complex mixture of fats, making it extremely challenging to separate its components (using chromatography) and to analyze their structures (using mass spectrometry). ARS scientists in Beltsville, Maryland, modified valve system allowed more dimensions of separation to be added to a commercially available instrument to provide three dimensional separation. The modified chromatographic system can provide greater separation of fatty acid fractions than previously possible. This research will provide new insights into the composition of cow’s milk.
7. Comprehensive analysis of food and supplements chemical composition. Many food plants and botanical supplements are only analyzed for their most significant or unique components. The remainder of the plant composition is largely unknown. ARS scientists in Beltsville, Maryland, used a systematic approach to the identify plant composition based on three steps: rapid chemical profiling for classification, full metabolomic profiling for a detailed analysis of the composition, and DNA sequencing for taxonomic identification of the plant material. A systematic, comprehensive analysis of plant materials is required to fully understand the relationship of composition, diet, and well-being.
Review Publications
Byrdwell, W.C. 2018. Blue jacaranda seed oil analyzed using comprehensive 2D-LC with quadruple parallel MS (LC2MS4). Journal of Chromatography. 56-64.
Luthria, D.L., Kotha, R.R., Natarajan, S.S., Wang, D. 2019. Compositional analysis of non-polar and polar metabolites in 14 soybeans using spectroscopy and chromatography tools. Foods. 8: 557-569. https://doi.org/10.3390/foods8110557.
Byrdwell, W.C. 2019. Timed relay contact closure controlled system for parallel second dimensions in multi-dimensional liquid chromatography. BMC Research Notes.12:477-482. https://doi.org/10.1186/s13104-019-4506-7.
Bergana, M., Adams, K., Harnly, J.M., Moore, J., Xie, Z. 2020. Non-targeted detection of milk powder adulteration by 1H NMR spectroscopy and conformity index analysis. Journal of Food Composition and Analysis. https://doi.org/10.1016/j.jfca.2019.01.016.
Geng, P., Sun, J., Chen, P., Li, Y., Peng, B., Harnly, J.M. 2020. A systematic approach to determine the impact of elevated CO2 levels on the chemical composition of wheat (Triticum aestivum). Journal of Cereal Science. 95:753. https://doi.org/10.1016/j.jcs.2020.103020.
Geng, P., Sun, J., Brand, E., Frame, J., Meissner, H., Stewart, J., Clark, S., Miller, J., Harnly, J.M., Chen, P., Gafner, S. 2020. Characterization of Maca (Lepidium meyenii/Lepidium peruvianum) using a mass spectral fingerprinting, metabolomic analysis, and genetic sequencing approach. Planta Medica. 169:453–468. https://doi.org/10.1055/a-1161-0372.
