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Therapeutic Properties of Fermented Foods and Beverages
Published in Megh R. Goyal, Preeti Birwal, Durgesh Nandini Chauhan, Herbs, Spices, and Medicinal Plants for Human Gastrointestinal Disorders, 2023
The essential cofactor involved in the biosynthesis of nucleotides is folate or vitamin B9 that are crucial for cellular replication and growth. S. cerevisiae produces high amount of folate per weight and is regarded as the rich dietary source of native folate.107 The mesophilic LAB cultures (such as: Lactobacillus, Leuconostoc, Pediococcus, Carnobacterium, Enterococcus, Streptococcus, Oenococcus, Tetragenococcus, Vagococcus, and Weissella34) especially Lactococcus spp. are able to produce vitamin-K by metabolization.83 Fermentation also enhances the bioavailability of vitamin B12 10-folds that helps in the formation and functioning of nervous system and formation of blood cells.188
Cell-Cell Communication in Lactic Acid Bacteria
Published in Marcela Albuquerque Cavalcanti de Albuquerque, Alejandra de Moreno de LeBlanc, Jean Guy LeBlanc, Raquel Bedani, Lactic Acid Bacteria, 2020
Emília Maria França Lima, Beatriz Ximena Valencia Quecán, Luciana Rodrigues da Cunha, Bernadette Dora Gombossy de Melo Franco, Uelinton Manoel Pinto
Lactic acid bacteria (LAB) are a diverse group of bacteria, yet with similar properties and all produce lactic acid as an end product of the fermentation process (Ferreira 2012). Taxonomically, the species are found in the phylum Firmicutes, Class Bacilli and order Lactobacillales, and include the genera Lactobacillus, Lactococcus, Leuconostoc, Oenococcus, Pediococcus, Streptococcus, Enterococcus, Tetragenococcus, Aerococcus, Carnobacterium, Vagococcus and Weissella (De Angelis et al. 2007, Reddy et al. 2008) which are all low guanine-cytosine (GC) content organisms (< 50%). However, some authors also consider Atopobium and Bifidobacterium genera, from the Actinobacteria phylum, as belonging to the LAB group for sharing some similar characteristics (Ferreira 2012, Wedajo 2015), despite the higher GC content.
Beneficial Lactic Acid Bacteria
Published in K. Balamurugan, U. Prithika, Pocket Guide to Bacterial Infections, 2019
At present most of LAB belong to phylum Firmicutes, order Lactobacillales, including genera Aerococcus, Alloiococcus, Carnobacterium, Enterococcus, Lactobacillus, Lactococcus, Leuconostoc, Oenococcus, Pediococcus, Streptococcus, Symbiobacterium, Tetragenococcus, Vagococcus, and Weissella. Species of Bifidobacterium genus from phylum Actinobacteria are referred to LAB in some cases because of their ability to produce lactic acid, but these bacterial groups are phylogenetically distinct (Biavati 2001; Liu et al. 2014).
Antioxidant properties of polyphenols from snow chrysanthemum (Coreopsis tinctoria) and the modulation on intestinal microflora in vitro
Published in Pharmaceutical Biology, 2022
Minghao Zhang, Naiyu Zhao, Minhao Xie, Deqiao Dong, Weilin Chen, Yuanpeng He, Dalin Yan, Haiyan Fu, Xinlin Liang, Li Zhou
SCPs were obtained by ultrasonic-assisted extraction. Ten phenolic compounds were identified by UPLC-QE Orbitrap/MS. Amongst them, marein, isookanin and cymaroside, were the major phenolics in SCPs. The antioxidant capacity of cymaroside was significantly weakest (p < 0.05) compared with marein and isookanin. The three polyphenols had significant effects on the intestinal microbial profiles and functions of the communities. They increased the relative abundances of Escherichia/Shigella, Enterococcus, Klebsiella, Streptococcus, Vagococcus, Citrobacter, and Odoribacter and isookanin notably increased the relative abundance of Bifidobacterium and Lactobacillus. The phenolics also had an impact on several metabolism pathways. This study helps consumers better understand the nutritional value of C. tinctoria, and further provides a scientific basis for the development of C. tinctoria and its products.
Type 2 diabetes, gut microbiome, and systems biology: A novel perspective for a new era
Published in Gut Microbes, 2022
Yoscelina Estrella Martínez-López, Diego A. Esquivel-Hernández, Jean Paul Sánchez-Castañeda, Daniel Neri-Rosario, Rodolfo Guardado-Mendoza, Osbaldo Resendis-Antonio
In another study using SparCC, it was found that alterations in GM are involved in the treatment of T2D with hyperlipidemia in a Chinese cohort of 450 subjects exposed to two clinical interventions: metformin and AMC (a Chinese herbal formula of Rhizoma Anemarrhenae, Momordica charantia, Coptis chinensis, Aloe vera, and red yeast rice).148,149 In the metformin-treated group, the authors noted a remarkable increase in Blautia spp, (SCFA producer), which is in line with other studies conducted on animals.90 Also, they observed a decline in Akkermansia in T2D Chinese subjects with metformin treatment. However, these findings do not agree with those of other studies on humans, where Akkermansia increases after metformin is consumed.84,118,150,151 This discrepancy might be explained when we take into account strain-specific functions; thus, the authors suggested further studies (such as molecular analysis the full ribosomal 16S gene and phylogenetic trees) to clarify this controversy.148,149 On the other hand, treatment with AMC increased the abundance of two genera related to butyrate production (i.e., Faecalibacterium and Roseburia).152 Interestingly, Faecalibacterium prausnitzii has been reported as a functionally important bacterium to prevent physiological damage through the production of butyrate and anti-inflammatory metabolites.153 Moreover, AMC had a stronger modulatory effect on the GM than metformin treatment in terms of improving IR and triglyceride levels. This can be explained by the synergistic effects of the multiple phytochemicals present in AMC.148 Concerning other diseases caused by T2D, the information is limited.154 Das et al. published an interesting study on the association between GM dysbiosis in T2D and diabetic retinopathy (DR) with an Indian cohort of 30 subjects. Regarding T2D subjects, the authors found positive associations between a chronic low-grade inflammatory state and pathogenic genera such as Gardnerella, Atopobium, Fusobacterium, Gemella, Halomonas, and Vagococcus. Moreover, and with DR participants, a reduction in the abundance of anti-inflammatory and probiotic bacteria in comparison to other genera was observed. However, in terms of the GM of T2D and DR, the authors did not report significant differences at the genus level.154
Integrating gut microbiome and host immune markers to understand the pathogenesis of Clostridioides difficile infection
Published in Gut Microbes, 2021
Shanlin Ke, Nira R. Pollock, Xu-Wen Wang, Xinhua Chen, Kaitlyn Daugherty, Qianyun Lin, Hua Xu, Kevin W. Garey, Anne J. Gonzales-Luna, Ciarán P. Kelly, Yang-Yu Liu
To analyze these patterns in more detail, we used NetShift39 to identify potentially important “driver” taxa responsible for the change of microbial correlations. In the NetShift pipeline, the common taxa present in both ‘control’ and ‘case’ sample sets with a minimum abundance threshold are extracted to construct the microbial correlation networks. Then the ‘driver taxa’ are identified based on their Neighbor Shift (NESH) scores and the Betweenness Centrality (BC) measures. In a nutshell, the NESH score of a taxon/node is minimum when the associated partners of this node are the same in both ‘case’ and ‘control’ networks, intermediate when there is only a subset of the associated partners present in the ‘case’ network, and maximum when a completely new set of associated partners appear in the ‘case’ network. The Betweenness Centrality of a taxon/node quantifies its involvement in connecting other nodes in the network. A taxon with an altered set of edges (identified by a high NESH score), while still being increasingly important (i.e., with higher scaled BC in the ‘case’ network than in the ‘control’ network), necessarily holds a key significance in microbial interplay and is identified as a ‘driver’ taxon. This analysis revealed 24 potential driver taxa linked with the change of microbial correlations between CDI and Asymptomatic Carriage groups (Supplementary Figure 1). The top driver taxa were Alistipes, Clostridioides, Desulfovibrio, Eggerthella, Erysipelatoclostridium, Klebsiella, Odoribacter, Proteus, [Ruminococcus]_torques_group, Streptococcus, Vagococcus and Veillonella. We then identified 24 genera as potential driver taxa underlying the change of microbial correlations between CDI and Non-CDI Diarrhea groups (Supplementary figure 2). The top driver taxa were Alistipes, Buttiauxella, Citrobacter, Clostridium_sensu_stricto_13, Desulfovibrio, Klebsiella, Oscillibacter, Phascolarctobacterium, Streptococcus and Veillonella. Finally, Netshift analysis revealed 38 potential driver taxa underlying the change of microbial correlations between CDI and Non-CDI groups. The top driver taxa were Bifidobacterium, Clostridioides, Klebsiella, Oscillibacter, Streptococcus and Veillonella (Supplementary Figure 3). Together, these results suggested that certain bacterial taxa (e.g., Clostridioides, Klebsiella, Streptococcus and Veillonella) could play an important role in driving the changes of microbial correlations in subjects with different C.difficile infection/colonization status.