Progress 05/15/20 to 05/14/24
Outputs
Target Audience:Bioprocessing and food engineers and scientists working on antioxidants, plant proteins, corn biofuel industries, antioxidant producers, and endusers. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Two PhD graduate student researchers (Ruijia Hu, Zhenjiao Du) and twopostdocs (partially funded from this project, Dr. Qing Jin, Dr. Xuanbo Liu) were involved and trained during this project on peptides production, characterization, application evaluation, and/or techno-economic analysis modeling. The researchers had opportunities to connect with peers and present their findings at various conferences and meetings, including the 26th Distillers Grains Symposium, 2022 AOCS Annual Meeting & Expo, 2023 AOCS Annual Meeting & Expo,Cereals & Grains 21 annual conference, Cereals & Grains 22 annual conference.Graduate student Ruijia Hu was awarded the Graduate Student Research Scholarship by the Distillers Grains Technology Council (DGTC), and she was invited and presented her research at the 26th Distillers Grains Symposium. How have the results been disseminated to communities of interest?The results have been disseminated through one PhD dissertation, five journal articles, and 11 conference papers and presentations. Particularly, the PI Dr. Li and the team were invited and presented their findings at various international, national, and regional conferences and meetings, including the Distillers Grains annual symposium, the Kansas Corn symposium, Cereals & Grains annual meetings, AOCS Annual meetings, and others. The team also interacted with various stakeholders and visitors from industries and discussed their findings. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
We conducted the extraction of peptide antioxidants using the DDGS residues immediately after the extraction of phenolic antioxidants with different optimized solvents (100% water, 50% acetone, 50% ethanol, 50% 2-proponal, 50% methanol, or 50% 1-proponal). The phenolics extracted with 50% acetone had the highest total phenolic content (67.54 mg GAE/g), followed by that extracted with 50% methanol (63.34 mg GAE./g). Hydrolyzing the residues with Alcalase at 0.1 Au/g addition generated promising protein hydrolysates as peptide antioxidants. The yield of peptide antioxidants was in the range of 16 to 21%, and the highest yield of 21% was achieved from the 50% methanol extracted DDGS. Overall, phenolic antioxidants from DDGS showed higher DPPH scavenging activity than the peptide antioxidants, but the peptide antioxidants had better Fe2+ chelating capacity than the phenolic antioxidants. Peptide antioxidants from the DDGS residues after 50% methanol extraction possessed the highest total phenolic content, and peptide antioxidant from the residues after 50% 2-proponal extraction had the highest DPPH scavenging activity. Emulsions containing either phenolic or peptide antioxidants showed slower oxidation trend with lower POV and TBARS values during 15 days of incubation compared to the control emulsion without any antioxidants. Phenolics and peptides prepared from 50% ethanol had better antioxidant performance in emulsion among all the DDGS antioxidants. The extracts also showed great promise when applied to oil or formulated pet food. The chemical composition of the phenolic antioxidants was identified using RP-HPLC/MS/MS. Results showed that sinapic acid was the dominant phenolic acid in all the extracts, and the extracts also contained trans-ferulic acid, syringic acid, vanillic acid, 4-hydrobenzoic acid, and p-coumaric acid. Peptide content in the peptide antioxidants was approximately 50-55%. The antioxidant potential of different types of corn, as well as the distribution of antioxidant compounds in different components of corn kernel, remain unknown. We determined total phenolic content (TPC), total flavonoid content (TFC), and total tannins content (TTC), and evaluated the antioxidant activities of 17 different corn kernels, including 6 varieties of field corn, 5 varieties of popcorn, and 5 varieties of sweet corn, as well as the bran, germ, and endosperm fractions. The range of free TPC observed in the 17 corn kernels was 270-600 μg GAE/g, and the range of bound TPC was 970-2020 μg GAE/g. Overall, sweet corn showed relatively higher TPC than the other two types of corn. The Kandy Korn (yellow sweet corn) showed the highest phenolic (2612 μg GAE/g) levels among all the investigated corn types. Ohio blue (blue) had the highest phenolic levels (2129 μg GAE/g) among the field corn varieties, and Strawberry (red) appeared to have the highest phenolic levels (2342 μg GAE/g) among the popcorn varieties. The soluble TFC ranged from 28 to 245 μg GE/g, and the insoluble TFC ranged from 23 to 67 μg GE/g. Strawberry (red popcorn) showed the highest TFC content of 297.09 μg GE/g in total. The range of free TTC observed among the 17 corn kernels was 133 to 1125 μg CE/g, and the bound TTC was in the range from 50 to 308 μg. Jimmy red (red fieldcorn) had the highest total TTC value (1258.33 μg CE/g). Antioxidant activities of free and bound phenolic extracts were evaluated using DPPH free radical scavenging activity and Fe2+ chelating capacity. According to TPC, TFC, TTC, and antioxidant activities, Kandy Korn (yellow sweet corn), Ohio blue (blue fieldcorn), and Strawberry (red popcorn) were selected for the separation and analysis of different kernel components. Overall, bran had the highest total phenolic content, followed by the germ, and endosperm had the lowest TPC. Both whole kernel and separated components were analyzed using UPLC-QTOF-MS/MS system for phenolic quantification and qualification detection (i.e., 4-hydroxybenzoic acid, vanillic acid, syringic acid, p-coumaric acid, trans-ferulic acid, and sinapic acid). Protein hydrolysates derived from corn gluten meal (CGM) and DDGS were produced using Neutrase and Alcalase enzymes. The antioxidant properties of these hydrolysates were assessed in bulk oils, ground pork, canine pet food, and pig feed by evaluating oxidation stability through peroxide value (PV) and thiobarbituric reactive substances (TBARS) measurements. Both CGM hydrolyzed with Alcalase (CPH-A) and Neutrase (CPH-N) exhibited stronger 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activity compared to DDGS hydrolyzed with Alcalase (DPH-A) and Neutrase (DPH-N). CPH-N was particularly effective in preventing lipid oxidation in corn oil and fish oil, surpassing other corn-derived antioxidants. The most effective reduction of lipid oxidation in ground meat was achieved with 2?g/kg of CPH-N. In pet food, 2% DPH-A significantly reduced lipid oxidation by 37.8% by the end of incubation, while 2% CPH-N in pig feed resulted in the greatest reduction of TBARS values compared to other treatments. No significant differences were observed in growth performance or plasma antioxidant levels between broilers fed DDGS or Alcalase-treated DDGS. Overall, CGM and DDGS protein hydrolysates show potential as natural antioxidants in food, pet food, and feed, offering good protection against lipid oxidation and enhancing product storage stability. Hydrolysates produced with Alcalase and Neutrase exhibited promising antioxidant capabilities. Our research supports the potential of corn by-product hydrolysates in improving oxidation stability across various food and feed models. Developing antioxidative and other bioactive peptides from food protein sources, including distillers grains, for nutraceutical and pharmaceutical applications is gaining momentum. Traditional wet lab methods can be time-consuming and require significant effort. With the advent of large-scale protein and peptide datasets and advanced machine learning techniques, artificial intelligence (AI)-based methods can accelerate the discovery of peptides with specific bioactivities and supplement traditional wet lab methods. We employed pre- trained a protein language model (ESM2) for peptide embeddings, and developed the UniDL4BioPep, a universal deep learning architecture based on ESM2 and convolutional neural network (CNN) for binary classification in peptide bioactivity, including antioxidant activity. The UniDL4BioPep performed better than existing state-of-the-art models in 15 out of 20 different peptide bioactivity prediction tasks, with higher accuracy, Mathews correlation coefficient, and area under the curve values. The newly developed model can be self-adaptive to predict any bioactivity of peptides with any length and achieve cutting-edge performance. Techno-economic analysis indicates that the new process for producing peptide powders incurs higher annual operating costs when using Neutrase ($49.8 million) or Flavourzyme ($141.3 million) compared to the traditional DDGS process ($11.2 million), with enzyme costs being the primary contributor. Despite these higher costs, the net profit per metric ton (MT) of DDGS using the modified Neutrase process ($696.3/MT DDGS) significantly exceeds that of the traditional process ($67.7/MT DDGS). In contrast, due to the higher price of food-grade Flavourzyme ($93.30/kg) compared to Neutrase ($22.7/kg), and the lower antioxidant yield with Flavourzyme, the profitability of the modified process using Flavourzyme is much lower ($31.0/MT DDGS).In conclusion,although the annual operating cost with antioxidant extraction is higher than the regular DDGS process, the net profit per each unit weight of DDGS canstill be better than that of the regular DDGS, contributed by the much higher values of the antioxidants.
Publications
- Type:
Theses/Dissertations
Status:
Published
Year Published:
2023
Citation:
Hu, Ruijia. "Developing and characterizing antioxidants and proteins from corn and its co-coproducts." PhD dissertation, Kansas State University, 2023.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2024
Citation:
Y. Li. AI-Empowered Discovery of Bioactive Peptides from Food Proteins. 2024, May 22-23, 2024, Plant Protein Innovation Center, University of Minnesota, MN.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Y. Li. Harnessing AI Language Models for Predicting Protein and Peptides (Bio)-functions. 4th AOCS China Section Conference, Haikou, China, Dec. 3-6, 2023.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Y. Li. Accelerating bioactive peptides discovery with AI-powered protein language models. 3rd International Symposium on Bioactive Peptides, Niagara Falls, Canada, Sept. 27-29th, 2023.
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Progress 05/15/22 to 05/14/23
Outputs
Target Audience:Bioprocessing engineers and scientists working on antioxidants, corn biofuel industries, antioxidant producers, and end-users. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Two graduate students and one postdoc (partially funded) were involved and trained during this project on antioxidant production, characterization, application evaluating, and/or techno-economic analysis modeling. How have the results been disseminated to communities of interest?The PI Dr. Li and graduate students presented and disseminated the project findings at the26th Distillers Grains Symposium, 2022 Cereals & Grains Association Annual Conference, 2023 Kansas Corn Symposium, and 2023 AOCS Annual Meeting. Several journal articles have been published. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
The antioxidant potential of different types of corn, as well as the distribution of antioxidant compounds in different components of corn kernel, remain unknown. We determined total phenolic content (TPC), total flavonoid content (TFC), and total tannins content (TTC), and evaluated the antioxidant activities of 17 different corn kernels, including 6 varieties of field corn, 5 varieties of popcorn, and 5 varieties of sweet corn, as well as the bran, germ, and endosperm fractions. The range of free TPC observed in the 17 corn kernels was 270-600 μg GAE/g, and the range of bound TPC was 970-2020 μg GAE/g. Overall, sweet corn showed relatively higher TPC than the other two types of corn. The Kandy Korn (yellow sweet corn) showed the highest phenolic (2612 μg GAE/g) levels among all the investigated corn types. Ohio blue (blue) had the highest phenolic levels (2129 μg GAE/g) among the field corn varieties, and Strawberry (red) appeared to have the highest phenolic levels (2342 μg GAE/g) among the popcorn varieties. The soluble TFC ranged from 28 to 245 μg GE/g, and the insoluble TFC ranged from 23 to 67 μg GE/g. Strawberry (red popcorn) showed the highest TFC content of 297.09 μg GE/g in total. The range of free TTC observed among the 17 corn kernels was 133 to 1125 μg CE/g, and the bound TTC was in the range from 50 to 308 μg. Jimmy red (red fieldcorn) had the highest total TTC value (1258.33 μg CE/g). Antioxidant activities of free and bound phenolic extracts were evaluated using DPPH free radical scavenging activity and Fe2+ chelating capacity. Among all the free phenolic extracts, the free phenolic from Silver King (white sweet corn) showed the highest DPPH scavenging activity (84%), and free phenolic from Alavon (white sweet corn) had the highest Fe2+ chelating capacity (69.15%). For the bound phenolic extracts, the bound phenolic from Avalon (white sweetcorn) had the highest DPPH scavenging activity (78.86%), and the bound phenolic from Kandy Korn (yellow sweet corn) had the highest Fe2+ chelating capacity. According to TPC, TFC, TTC, and antioxidant activities, Kandy Korn (yellow sweet corn), Ohio blue (blue fieldcorn), and Strawberry (red popcorn) were selected for the separation and analysis of different kernel components. Overall, bran had the highest total phenolic content, followed by the germ, and endosperm had the lowest TPC. Both whole kernel and separated components were analyzed using UPLC-QTOF-MS/MS system for phenolic quantification and qualification detection (i.e., 4-hydroxybenzoic acid, vanillic acid, syringic acid, p-coumaric acid, trans-ferulic acid, and sinapic acid). The findings were presented at the 2022 Cereals & Grains Association Annual Conference, as well as the 2023 Kansas Corn Symposium. Developing antioxidative and other bioactive peptides from food protein sources, including distillers grains, for nutraceutical and pharmaceutical applications is gaining momentum. Traditional wet lab methods can be time-consuming and require significant effort. With the advent of large-scale protein and peptide datasets and advanced machine learning techniques, artificial intelligence (AI)-based methods can accelerate the discovery of peptides with specific bioactivities and supplement traditional wet lab methods. We employed pre- trained a protein language model (ESM2) for peptide embeddings, and developed the UniDL4BioPep, a universal deep learning architecture based on ESM2 and convolutional neural network (CNN) for binary classification in peptide bioactivity, including antioxidant activity. The UniDL4BioPep performed better than existing state-of-the-art models in 15 out of 20 different peptide bioactivity prediction tasks, with higher accuracy, Mathews correlation coefficient, and area under the curve values. The newly developed model can be self-adaptive to predict any bioactivity of peptides with any length and achieve cutting-edge performance. The findings were presented at the 2023 AOCS Annual Meeting as an invited talk.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Du, Z., Ding, X., Xu, Y., Li, Y.*. 2023. UniDL4BioPep: A universal deep learning architecture for binary classification in peptide bioactivity. Briefings in Bioinformatics, bbad135, https://doi.org/10.1093/bib/bbad135.
- Type:
Journal Articles
Status:
Published
Year Published:
2023
Citation:
Du, Z., Comer, J., Li, Y.*. 2023. Bioinformatics approaches to discovering food-derived bioactive peptides: Reviews and perspectives. TrAC Trends in Analytical Chemistry. https://doi.org/10.1016/j.trac.2023.117051.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2022
Citation:
R. Hu, Y. Li*. Comparative evaluation of phenolic profiles and antioxidant activates of different corns. Cereals & Grains 22, Bloomington, Minnesota, Nov. 9-11, 2022. (poster)
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2022
Citation:
R. Hu, Y. Li*. Developing and characterizing antioxidants from corn distillers grains. Cereals & Grains 22, Bloomington, Minnesota, Nov. 9-11, 2022. (poster)
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Y. Li. Accelerating Bioactive Peptides Discovery from Food Proteins Through AI. 2023 AOCS Annual Meeting & Expo, April 30May 3, 2023, Colorado Convention Center, Denver, Colorado, USA. (Invited)
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
Du, Z. and Li, Y.*. 2022. Review and perspective on bioactive peptides: A roadmap for research, development, and future opportunities. Journal of Agriculture and Food Research, 9, 100353. https://doi.org/10.1016/j.jafr.2022.100353
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Progress 05/15/21 to 05/14/22
Outputs
Target Audience:Bioprocessing engineers and scientists working on antioxidants, corn biofuel industries, antioxidant producers, and end-users. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Two graduate students and one postdoc (partially funded) were involved and trained during this project on peptides production, characterization, application evaluation, and/or techno-economic analysis modeling. The PI Dr. Li was invited to present the project findings at the Center for Sorghum Improvement seminar series with 40-50 attendees, and at the 2022 Sorghum Improvement Conference of North America (SICNA) conference with over 100 attendees. Graduate student Ruijia Hu was awarded the Graduate Student Research Scholarship by the Distillers Grains Technology Council (DGTC), and she was invited and presented her research at the 26th Distillers Grains Symposium. Ruijia also attended and presented the research at the Cereals & Grains 21 annual conference. Zhenjiao Du presented antioxidant research at the 2022 AOCS Annual Meeting & Expo. How have the results been disseminated to communities of interest?One journal article has been published. A total of six presentations were delivered at the 26th Distillers Grains Symposium, AOCS Annual Conference, Cereals and Grains Association Annual Conference, and the SICNA conference. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
We conducted the extraction of peptide antioxidants using the DDGS residues immediately after the extraction of phenolic antioxidants with different optimized solvents (100% water, 50% acetone, 50% ethanol, 50% 2-proponal, 50% methanol, or 50% 1-proponal). The phenolics extracted with 50% acetone had the highest total phenolic content (67.54 mg GAE/g), followed by that extracted with 50% methanol (63.34 mg GAE./g). Hydrolyzing the residues with Alcalase at 0.1 Au/g addition generated promising protein hydrolysates as peptide antioxidants. The yield of peptide antioxidants was in the range of 16 to 21%, and the highest yield of 21% was achieved from the 50% methanol extracted DDGS. Overall, phenolic antioxidants from DDGS showed higher DPPH scavenging activity than the peptide antioxidants, but the peptide antioxidants had better Fe2+ chelating capacity than the phenolic antioxidants. Peptide antioxidants from the DDGS residues after 50% methanol extraction possessed the highest total phenolic content, and peptide antioxidant from the residues after 50% 2-proponal extraction had the highest DPPH scavenging activity. Emulsions containing either phenolic or peptide antioxidants showed slower oxidation trend with lower POV and TBARS values during 15 days of incubation compared to the control emulsion without any antioxidants. Phenolics and peptides prepared from 50% ethanol had better antioxidant performance in emulsion among all the DDGS antioxidants. The extracts also showed great promise when applied to oil or formulated pet food. The chemical composition of the phenolic antioxidants was identified using RP-HPLC/MS/MS. Results showed that sinapic acid was the dominant phenolic acid in all the extracts, and the extracts also contained trans-ferulic acid, syringic acid, vanillic acid, 4-hydrobenzoic acid, and p-coumaric acid. Peptide content in the peptide antioxidants was approximately 50-55%. Techno-economic analysis showed that, although the annual operating cost with antioxidant extraction is higher than the regular DDGS process, the net profit per each unit weight of DDGS is still much better than that of the regular DDGS, contributed by the much higher values of the antioxidants. The findings have been communicated to various stakeholders to promote the technology. The PhD student (Ms. Ruijia Hu) working on this project was awarded the Graduate Student Research Scholarship by the Distillers Grains Technology Council (DGTC), and she was invited and presented her research at the 26th Distillers Grains Symposium.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2022
Citation:
Y. Li. Grain Sorghum Derived Proteins, Peptides, and Polyphenols. The Sorghum Improvement Conference of North America (SICNA). Dallas, TX. March 28-30, 2022
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2022
Citation:
Z. Du, Y. Li. Quantitative structure-activity relationship study on antioxidant dipeptides. 2022 AOCS Annual Meeting & Expo, Atlanta, Georgia. May 1-4, 2022.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2022
Citation:
Z. Du, D. Wang, Y. Li. Comprehensive evaluation and comparison of machine learning methods in QSAR modeling of antioxidant tripeptides. 2022 AOCS Annual Meeting & Expo, Atlanta, Georgia. May 1-4, 2022.
- Type:
Journal Articles
Status:
Published
Year Published:
2022
Citation:
R. Hu, J. Xu, G. Qi, W. Wang, X. S. Sun, Y. Li. 2022. Antioxidative hydrolysates from corn gluten meal may effectively reduce lipid oxidation and inhibit HepG2 cancer cell growth. Journal of Agriculture and Food Research, 7, 100252. https://doi.org/10.1016/j.jafr.2021.100252
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
J. Zhao, D. Wang, Y. Li. 2021. Proteins in dried distillers grains with solubles (DDGS): A review of animal feed value and potential non-food uses. Journal of the American Oil Chemists' Society. 98, 10, 957-968. https://doi.org/10.1002/aocs.12516.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2021
Citation:
R. Hu, Y. Li. Preparation, characterization, and application of antioxidative peptides from enzymatically hydrolyzed corn gluten meal. Cereals & Grains 21, Nov. 17-18, 2021 (Virtual meeting)
- Type:
Conference Papers and Presentations
Status:
Accepted
Year Published:
2022
Citation:
R. Hu, Y. Li*. Developing Antioxidants from Corn Distillers Dried Grains with Solubles (DDGS). 26th Distillers Grains Symposium. Omaha, Nebraska. May 11 & 12, 2022.
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Progress 05/15/20 to 05/14/21
Outputs
Target Audience:Bioprocessing engineers and scientists working on antioxidants, corn biofuel industries, antioxidant producers and end-users. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?One graduate student focusing on antioxidant extraction and characterization and one part-time postdoc focusing on techno-economic analysis are being trained duringthis project. How have the results been disseminated to communities of interest?Biofuel manufacturers, antioxidants producers and formulators, and other related industriesare being contacted and communicated to identify potential collaboration opportunities. What do you plan to do during the next reporting period to accomplish the goals?We will continue to optimize phenolic and peptide antioxidant extraction, characterize their properties andperformances, optimize the techno-economic analysis model, and work with stakeholders to disseminate our findings.
Impacts
What was accomplished under these goals?
We evaluated the extraction efficiency of different types (ethanol, methanol, acetone, 1-proponal, and 2-proponal) and concentrations (0, 25%, 50%, 75% and 100% v/ v) of GRAS solvents for the extraction of phenolic antioxidantsfrom DGs, and analyzed the extraction yield, total phenolic content, DPPH scavenging activity, metal chelating activity, and oxygen radical absorbance capacity. We foundthatusing 75% acetone, 75% ethanol, 75% methanol, 50% 1-proponal, or 50% 2-proponal resulted in phenolic extracts with a better balance of yield and antioxidant performance. A draft techno-economic analysis modelincludinga conceptual process design using a process flow diagram, detailed process modeling of material inputs and outputs, and energy balance calculations, has been established using SuperPro Designer v9.0 and being further optimized. Biofuel manufacturers, antioxidants producers, and other related industriesare being contacted and communicatedto identify potential collaboration opportunities.
Publications
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