Search results for: tenericutes

Authors: Anna D. Kotrova, Alexandr N. Shishkin, Elena I. Ermolenko

Abstract:

The aim. To study the quantitative and qualitative colon bacteria ratio from patients with metabolic syndrome. Materials and methods. Fecal samples from patients of 2 groups were identified and analyzed: the first group was formed by patients with metabolic syndrome, the second one - by healthy individuals. The metagenomics method was used with the analysis of 16S rRNA gene sequences. The libraries of the variable sites (V3 and V4) gene 16S RNA were analyzed using the MiSeq device (Illumina). To prepare the libraries was used the standard recommended by Illumina, a method based on two rounds of PCR. Results. At the phylum level in the microbiota of patients with metabolic syndrome compared to healthy individuals, the proportion of Tenericutes was reduced, the proportion of Actinobacteria was increased. At the genus level, in the group with metabolic syndrome, relative to the second group was increased the proportion of Lachnospira. Conclusion. Changes in the colon bacteria ratio in the gut microbiota of patients with metabolic syndrome were found both at the type and the genus level. In the metabolic syndrome group, there is a decrease in the proportion of bacteria that do not have a cell wall. To confirm the revealed microbiota features in patients with metabolic syndrome, further study with a larger number of samples is required.

Keywords: gut microbiota, metabolic syndrome, metagenomics, tenericutes

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Authors: Yan Li, Qingxiang Meng, Bo Zhou, Zhenming Zhou

Abstract:

The objective of this study was to compare the effects of ensiled mulberry leaves (EML), and sun-dried mulberry fruit pomace (SMFP) on fecal bacterial communities in Simmental crossbred finishing steers fed the following 3 diets: a standard TMR diet, standard diet containing EML and standard diet containing SMFP, and the diets had similar protein and energy levels. Bacterial communities in the fecal content were analyzed using Illumina Miseq sequencing of the V4 region of the 16S rRNA gene amplification. Quantitative real-time PCR was used to detect the selected bacterial species in the feces. Most of the sequences were assigned to phyla Firmicutes (56.67%) and Bacteroidetes(35.90%), followed by Proteobacteria(1.86%), Verrucomicrobia(1.80%) and Tenericutes(1.37%). And the predominant genera included the 5-7N15 (5.91%), CF231 (2.49%), Oscillospira (2.33%), Paludibacter (1.23%) and Akkermansia(1.11%). As for the treatments, no significant differences were observed in Firmicutes (p = 0.28), Bacteroidetes (p = 0.63), Proteobacteria (p = 0.46), Verrucomicrobia (p = 0.17) and Tenericutes (p = 0.75). On the genus level, classified genera with high abundance (more than 0.1%) mainly came from two phyla: Bacteroidetes and Firmicutes. Also no differences were observed in most genera level, 5-7N15 (p = 0.21), CF231 (p = 0.62), Oscillospira (p = 0.9), Paludibacter (p = 0.33) and Akkermansia (p = 0.37), except that rc4-4 were lower in the CON and SMFP groups compared to the EML animals (p = 0.02). Additionally, there were no differences in richness estimate and diversity indices (p > 0.16), and treatments had no significant effect on most selected bacterial species in the fecal (p > 0.06), except that Ruminococcus albus were higher in the EML group (p < 0.01) and Streptococcus bovis were lower in the CON group (p < 0.01). In conclusion, diets supplemented with EML and SMFP have little influence on fecal bacterial community composition in finishing steers.

Keywords: fecal bacteria community composition, sequencing, ensiled mulberry leaves (EML), sun-dried mulberry fruit pomace (SMFP)

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Authors: John N. Idenyi, Hadimundeen Abdallah, Abigeal D. Adeyemi, Jonathan C. Eya

Abstract:

Gut microbiomes play a significant role in the growth, metabolism, and health of fish. However, we know very little about the interactive effects of variations in dietary composition and temperature on rainbow trout gut microbiota. Exactly 288 rainbow trout weighing 45.6g ± 0.05 (average ± SD) were fed four isocaloric, isolipidic, and isonitrogenous diets comprising 40% crude protein and 20% crude lipid and formulated as 100 % animal-based protein (AP) and a blend of 50 fish oil (FO)/50 camelina oil (CO), 100 % AP and100 % CO, 100 % plant-based protein (PP) and a blend of 50FO/50CO or 100 % PP and 100 % CO in 14 or 18°C for 150 days. Gut content was analyzed using 16S rRNA gene and shotgun sequencing. The most abundant phyla identified regardless of diet were Tenericutes, Firmicutes, Proteobacteria, Spirochaetes, Bacteroidetes, and Actinobacteria, while Aeromonadaceae and Enterobacteriaceae were dominant families in 18°C. Moreover, gut microbes were dominated by genes relating to an amino acid, carbohydrate, fat, and energy metabolisms and influenced by temperature. The shared functional profiles for all the diets suggest that plant protein sources in combination with CO could be as good as the fish meal with 50/50 FO & CO in rainbow trout farming.

Keywords: aquafeed, aquaculture, microbiome, rainbow trout

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Authors: Irina M. Kolesnikova, Andrey M. Gaponov, Sergey A. Roumiantsev, Tatiana V. Grigoryeva, Dilyara R. Khusnutdinova, Dilyara R. Kamaldinova, Alexander V. Shestopalov

Abstract:

Background. Obese patients have unequal risks of metabolic disorders. It is accepted to distinguish between metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO). MUHO patients have a high risk of metabolic disorders, insulin resistance, and diabetes mellitus. Among the other things, the gut microbiota also contributes to the development of metabolic disorders in obesity. Obesity is accompanied by significant changes in the gut microbial community. In turn, bacterial translocation from the intestine is the basis for the blood microbiome formation. The aim was to study the features of the blood microbiome in patients with various metabolic types of obesity. Patients, materials, methods. The study included 116 healthy donors and 101 obese patients. Depending on the metabolic type of obesity, the obese patients were divided into subgroups with MHO (n=36) and MUHO (n=53). Quantitative and qualitative assessment of the blood microbiome was based on metagenomic analysis. Blood samples were used to isolate DNA and perform sequencing of the variable v3-v4 region of the 16S rRNA gene. Alpha diversity indices (Simpson index, Shannon index, Chao1 index, phylogenetic diversity, the number of observed operational taxonomic units) were calculated. Moreover, we compared taxa (phyla, classes, orders, and families) in terms of isolation frequency and the taxon share in the total bacterial DNA pool between different patient groups. Results. In patients with MHO, the characteristics of the alpha-diversity of the blood microbiome were like those of healthy donors. However, MUHO was associated with an increase in all diversity indices. The main phyla of the blood microbiome were Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria. Cyanobacteria, TM7, Thermi, Verrucomicrobia, Chloroflexi, Acidobacteria, Planctomycetes, Gemmatimonadetes, and Tenericutes were found to be less significant phyla of the blood microbiome. Phyla Acidobacteria, TM7, and Verrucomicrobia were more often isolated in blood samples of patients with MUHO compared with healthy donors. Obese patients had a decrease in some taxonomic ranks (Bacilli, Caulobacteraceae, Barnesiellaceae, Rikenellaceae, Williamsiaceae). These changes appear to be related to the increased diversity of the blood microbiome observed in obesity. An increase of Lachnospiraceae, Succinivibrionaceae, Prevotellaceae, and S24-7 was noted for MUHO patients, which, apparently, is explained by a magnification in intestinal permeability. Conclusion. Blood microbiome differs in obese patients and healthy donors at class, order, and family levels. Moreover, the nature of the changes is determined by the metabolic type of obesity. MUHO linked to increased diversity of the blood microbiome. This appears to be due to increased microbial translocation from the intestine and non-intestinal sources.

Keywords: blood microbiome, blood bacterial DNA, obesity, metabolically healthy obesity, metabolically unhealthy obesity

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