Oona Koivisto
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Oona Koivisto has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Andrea Hanel
School of Medicine, Institute of Biomedicine, University of Eastern Finland, FI-70211 Kuopio, Finland
1 shared publication - Arto Koistinen
Department of Technical Physics, University of Eastern Finland, PO Box 1627, Kuopio FI-70211, Finland
1 shared publication - Carlos Gómez-Gallego
University of Eastern Finland
1 shared publication - Carsten Carlberg
InLife Institute of Animal Reproduction and Food Research, Polish Academy of Sciences
1 shared publication - Kaisa Raninen
Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70210 Kuopio, Finland
1 shared publication - Marjukka Kolehmainen
Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
1 shared publication
Latest Publications
- Open Access
- 27 November 2023
- Published by MDPI AG in Proceedings
- Vol. 91 (1) , 90
Malting of Barley and Wheat Grains Impacts Their Metabolic Profiles in a Model of In Vitro Colonic Fermentation
Background and objectives: Malting is a germination process that alters the composition of cereal grains and can impact the digestion of various nutrients included in whole-grain cereals. This can have a further impact on the composition of dietary fiber fractions fermented by the gut microbiota. We investigated the impact of malting with barley (Hordeum vulgare) and wheat (Triticum aestivum) grains on gut microbial metabolites during in vitro colonic fermentation in a model of human gut. Methods: Raw and malted barley and wheat grains went through in vitro gastric and intestinal digestions and a 24 h in vitro colonic fermentation mimicking human intestinal activities. Metabolite analysis was performed using nontargeted gas chromatography-mass spectrometry (GC-MS) optimized for the analysis of in vitro gut fermentation samples. Results: Multiple metabolites, including amino acids and their derivates (e.g., leucine and γ-aminobutyric acid), biogenic amines (e.g., tyramine, histamine, and putrescine), sugars and their derivates (e.g., fructose and galactinol), fatty acids and associated metabolites (e.g., glycerol and 2-aminoethanol), and energy metabolism-associated compounds (e.g., lactic acid) from raw and malted cereals were identified. The metabolite profiles differed significantly between cereal species and between raw and malted grains. Furthermore, the metabolite profiles changed during the fermentation. At 0 h, there was less variation between the metabolite profiles of raw cereals than malted cereals. At 24 h, the difference between malted barley and wheat was even more pronounced, but raw barley and wheat differed more from each other than at 0 h. Malting increased the initial sugar and sugar derivative levels in the cereals, as expected. However, levels of most amino acids and their derivates were significantly increased after the 24 h in vitro colonic fermentation. Discussion: The malting of cereal grains seems to influence the metabolites produced by the gut microbiota during colonic fermentation. Understanding how cereals and different processing methods affect gut microbial metabolism can help shed light on their microbial fermentation-mediated health impacts. The optimized GC-MS method used in this study was able to differentiate the different sample types and is thus an excellent tool for monitoring gut microbial metabolite profiles.
- 27 November 2023
- Published by MDPI AG in Proceedings
- Vol. 91 (1) , 90
Open AccessMalting of Barley and Wheat Grains Impacts Their Metabolic Profiles in a Model of In Vitro Colonic Fermentation
Background and objectives: Malting is a germination process that alters the composition of cereal grains and can impact the digestion of various nutrients included in whole-grain cereals. This can have a further impact on the composition of dietary fiber fractions fermented by the gut microbiota. We investigated the impact of malting with barley (Hordeum vulgare) and wheat (Triticum aestivum) grains on gut microbial metabolites during in vitro colonic fermentation in a model of human gut. Methods: Raw and malted barley and wheat grains went through in vitro gastric and intestinal digestions and a 24 h in vitro colonic fermentation mimicking human intestinal activities. Metabolite analysis was performed using nontargeted gas chromatography-mass spectrometry (GC-MS) optimized for the analysis of in vitro gut fermentation samples. Results: Multiple metabolites, including amino acids and their derivates (e.g., leucine and γ-aminobutyric acid), biogenic amines (e.g., tyramine, histamine, and putrescine), sugars and their derivates (e.g., fructose and galactinol), fatty acids and associated metabolites (e.g., glycerol and 2-aminoethanol), and energy metabolism-associated compounds (e.g., lactic acid) from raw and malted cereals were identified. The metabolite profiles differed significantly between cereal species and between raw and malted grains. Furthermore, the metabolite profiles changed during the fermentation. At 0 h, there was less variation between the metabolite profiles of raw cereals than malted cereals. At 24 h, the difference between malted barley and wheat was even more pronounced, but raw barley and wheat differed more from each other than at 0 h. Malting increased the initial sugar and sugar derivative levels in the cereals, as expected. However, levels of most amino acids and their derivates were significantly increased after the 24 h in vitro colonic fermentation. Discussion: The malting of cereal grains seems to influence the metabolites produced by the gut microbiota during colonic fermentation. Understanding how cereals and different processing methods affect gut microbial metabolism can help shed light on their microbial fermentation-mediated health impacts. The optimized GC-MS method used in this study was able to differentiate the different sample types and is thus an excellent tool for monitoring gut microbial metabolite profiles.
- Open Access
Key Vitamin D Target Genes with Functions in the Immune System
The biologically active form of vitamin D3, 1α,25-dihydroxyvitamin D3 (1,25(OH)2D3), modulates innate and adaptive immunity via genes regulated by the transcription factor vitamin D receptor (VDR). In order to identify the key vitamin D target genes involved in these processes, transcriptome-wide datasets were compared, which were obtained from a human monocytic cell line (THP-1) and peripheral blood mononuclear cells (PBMCs) treated in vitro by 1,25(OH)2D3, filtered using different approaches, as well as from PBMCs of individuals supplemented with a vitamin D3 bolus. The led to the genes ACVRL1, CAMP, CD14, CD93, CEBPB, FN1, MAPK13, NINJ1, LILRB4, LRRC25, SEMA6B, SRGN, THBD, THEMIS2 and TREM1. Public epigenome- and transcriptome-wide data from THP-1 cells were used to characterize these genes based on the level of their VDR-driven enhancers as well as the level of the dynamics of their mRNA production. Both types of datasets allowed the categorization of the vitamin D target genes into three groups according to their role in (i) acute response to infection, (ii) infection in general and (iii) autoimmunity. In conclusion, 15 genes were identified as major mediators of the action of vitamin D in innate and adaptive immunity and their individual functions are explained based on different gene regulatory scenarios.
Open AccessKey Vitamin D Target Genes with Functions in the Immune System
The biologically active form of vitamin D3, 1α,25-dihydroxyvitamin D3 (1,25(OH)2D3), modulates innate and adaptive immunity via genes regulated by the transcription factor vitamin D receptor (VDR). In order to identify the key vitamin D target genes involved in these processes, transcriptome-wide datasets were compared, which were obtained from a human monocytic cell line (THP-1) and peripheral blood mononuclear cells (PBMCs) treated in vitro by 1,25(OH)2D3, filtered using different approaches, as well as from PBMCs of individuals supplemented with a vitamin D3 bolus. The led to the genes ACVRL1, CAMP, CD14, CD93, CEBPB, FN1, MAPK13, NINJ1, LILRB4, LRRC25, SEMA6B, SRGN, THBD, THEMIS2 and TREM1. Public epigenome- and transcriptome-wide data from THP-1 cells were used to characterize these genes based on the level of their VDR-driven enhancers as well as the level of the dynamics of their mRNA production. Both types of datasets allowed the categorization of the vitamin D target genes into three groups according to their role in (i) acute response to infection, (ii) infection in general and (iii) autoimmunity. In conclusion, 15 genes were identified as major mediators of the action of vitamin D in innate and adaptive immunity and their individual functions are explained based on different gene regulatory scenarios.