Immunomodulatory activity of Alaska pollock hydrolysates obtained by glutamic acid biosensor – Artificial neural network and the identification of its active central fragment
The glutamic acid biosensor and artificial neural network (GLU-ANN) was employed to monitor the hydrolysis of Alaska pollock protein for production of immunomodulatory peptides. The relative error of GLU-ANN was in the range of 0.23% to 2.81%. The target pollock hydrolysates (PFH) were prepared usin...
| Published in: | Journal of Functional Foods |
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| Main Authors: | , , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Elsevier
2016
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| Subjects: | |
| Online Access: | https://doi.org/10.1016/j.jff.2016.03.033 https://doaj.org/article/cf50e6741c904c9eb6763e20590c3bb9 |
| Summary: | The glutamic acid biosensor and artificial neural network (GLU-ANN) was employed to monitor the hydrolysis of Alaska pollock protein for production of immunomodulatory peptides. The relative error of GLU-ANN was in the range of 0.23% to 2.81%. The target pollock hydrolysates (PFH) were prepared using GLU-ANN, which significantly enhanced humoral, cellular, and non-specific immunity in immunosuppressed mice, induced by hydrogenated cortisone (p < 0.05). In addition, treatment with PFH significantly increased the production of interleukin (IL)-2, IL-4, and IL-6 in immunosuppressed mice (p < 0.05), while interferon-gamma (IFN-γ) showed no significant change. The active central fragment that exhibited the highest lymphocyte proliferation rates was further purified using ion exchange chromatography, gel filtration chromatography, and reversed-phase high performance liquid chromatography (RP-HPLC). The amino acid sequence of this fragment was as follows: Pro-Thr-Gly-Ala-Asp-Tyr (PTGADY). Therefore, PFH shows promise as a potent immunomodulator with potential applications in functional food. |
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