In Silico Modeling of Metabolic Pathways in Probiotic Microorganisms for Functional Food Biotechnology
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| Veröffentlicht in: | Fermentation vol. 11, no. 8 (2025), p. 458-484 |
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| 001 | 3244012733 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2311-5637 | ||
| 024 | 7 | |a 10.3390/fermentation11080458 |2 doi | |
| 035 | |a 3244012733 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Baimakhanova, Baiken B |u LLP “Research and Production Center for Microbiology and Virology”, Almaty 050010, Kazakhstan; bbbayken@mail.ru (B.B.B.); a.sadanov1951@gmail.com (A.K.S.); iratnikova@list.ru (I.A.R.); s_orazymbet@inbox.ru (S.E.O.) | |
| 245 | 1 | |a In Silico Modeling of Metabolic Pathways in Probiotic Microorganisms for Functional Food Biotechnology | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Recent advances in computational biology have provided powerful tools for analyzing, modeling, and optimizing probiotic microorganisms, thereby supporting their development as promising agents for improving human health. The essential role of the microbiota in regulating physiological processes and preventing disease has driven interest in the rational design of next-generation probiotics. This review highlights progress in in silico approaches for enhancing the functionality of probiotic strains. Particular attention is given to genome-scale metabolic models, advanced simulation algorithms, and AI-driven tools that provide deeper insight into microbial metabolism and enable precise probiotic optimization. The integration of these methods with multi-omics data has greatly improved our ability to predict strain behavior and design probiotics with specific health benefits. Special focus is placed on modeling probiotic–prebiotic interactions and host–microbiome dynamics, which are essential for the development of functional food products. Despite these achievements, key challenges remain, including limited model accuracy, difficulties in simulating complex host–microbe systems, and the absence of unified standards for validating in silico-optimized strains. Addressing these gaps requires the development of integrative modeling platforms and clear regulatory frameworks. This review provides a critical overview of current advances, identifies existing barriers, and outlines future directions for the application of computational strategies in probiotic research. | |
| 653 | |a Physiology | ||
| 653 | |a Fermentation | ||
| 653 | |a Functional foods & nutraceuticals | ||
| 653 | |a Pathogens | ||
| 653 | |a Probiotics | ||
| 653 | |a Metabolic pathways | ||
| 653 | |a Microbiota | ||
| 653 | |a Disease | ||
| 653 | |a Biotechnology | ||
| 653 | |a Immune response | ||
| 653 | |a Linear programming | ||
| 653 | |a Genomes | ||
| 653 | |a Computer applications | ||
| 653 | |a Metabolism | ||
| 653 | |a Enzymes | ||
| 653 | |a Microorganisms | ||
| 653 | |a Strains (organisms) | ||
| 653 | |a Metabolites | ||
| 653 | |a Microbiomes | ||
| 700 | 1 | |a Sadanov, Amankeldi K |u LLP “Research and Production Center for Microbiology and Virology”, Almaty 050010, Kazakhstan; bbbayken@mail.ru (B.B.B.); a.sadanov1951@gmail.com (A.K.S.); iratnikova@list.ru (I.A.R.); s_orazymbet@inbox.ru (S.E.O.) | |
| 700 | 1 | |a Ratnikova, Irina A |u LLP “Research and Production Center for Microbiology and Virology”, Almaty 050010, Kazakhstan; bbbayken@mail.ru (B.B.B.); a.sadanov1951@gmail.com (A.K.S.); iratnikova@list.ru (I.A.R.); s_orazymbet@inbox.ru (S.E.O.) | |
| 700 | 1 | |a Baimakhanova, Gul B |u LLP “Research and Production Center for Microbiology and Virology”, Almaty 050010, Kazakhstan; bbbayken@mail.ru (B.B.B.); a.sadanov1951@gmail.com (A.K.S.); iratnikova@list.ru (I.A.R.); s_orazymbet@inbox.ru (S.E.O.) | |
| 700 | 1 | |a Orasymbet, Saltanat E |u LLP “Research and Production Center for Microbiology and Virology”, Almaty 050010, Kazakhstan; bbbayken@mail.ru (B.B.B.); a.sadanov1951@gmail.com (A.K.S.); iratnikova@list.ru (I.A.R.); s_orazymbet@inbox.ru (S.E.O.) | |
| 700 | 1 | |a Amitova, Aigul A |u Department of Chemical and Biochemical Engineering, Geology and Oil-Gas Business Institute Named After K. Turyssov, Satbayev University, Almaty 050043, Kazakhstan; aikkash@mail.ru | |
| 700 | 1 | |a Aitkaliyeva, Gulzat S |u Department of Chemical and Biochemical Engineering, Geology and Oil-Gas Business Institute Named After K. Turyssov, Satbayev University, Almaty 050043, Kazakhstan; aikkash@mail.ru | |
| 700 | 1 | |a Kakimova, Ardak B |u Department of Chemical and Biochemical Engineering, Geology and Oil-Gas Business Institute Named After K. Turyssov, Satbayev University, Almaty 050043, Kazakhstan; aikkash@mail.ru | |
| 773 | 0 | |t Fermentation |g vol. 11, no. 8 (2025), p. 458-484 | |
| 786 | 0 | |d ProQuest |t Biological Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3244012733/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3244012733/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3244012733/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |