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Selection of fast and slow growing bacteria from fecal microbiota using continuous culture with changing dilution rate.

ABSTRACT: Background: Nutrient and energy metabolism in human colon depends on bacterial growth rate that is determined by the colonic transit rate. Objective: A novel approach, De-stat culture was used to distinguish the fast and slow growing sub-populations from fecal microbiota. Design: The enrichment and metabolism of bacteria from pooled fecal cultures of children was studied at dilution rates D = 0.2-0.0 1/h in mucin-supplemented media containing either arabinogalactan or apple pectin. Results: The study revealed clear differentiation of the fecal microbiota at higher (above 0.1 1/h) and lower (below 0.1 1/h) dilution rates, along with metabolic changes. Similarity of the fast and slow growing bacteria was observed in two different fecal pools and on both substrates, suggesting the dilution rate as the main triggering parameter for selection of bacteria. At high dilution rates, the species Collinsella aerofaciens, Dorea longicatena, Escherichia coli, Lachnoclostridium torques, and different Bacteroides (B. caccae, B. fragilis, B. ovatus, B. thetaiotaomicron, B. vulgatus) were dominant in both media variants. At low dilution rates, Akkermansia muciniphila, Eisenbergiella tayi, Negativicoccus succinivorans, and a group of Ruminococcaceae became dominant in both media and in both fecal pools. This change in bacterial population accompanied by the increased production of propionic and butyric acids as well as higher consumption of alanine and branched chain amino acids at low dilution rates. Conclusions: The study suggests that specific growth rate has important effect on the dynamics of colon microbiota. Manipulation of the proportions of fast and slow growing gut bacteria through modulation of the transit rate could be a target in human nutrition studies. The De-stat study would enable to predict changes in microbiota composition associated with the decrease or increase of the colonic transit rate.

SUBMITTER: Adamberg K

PROVIDER: S-EPMC6282430 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Diverse microbial communities colonizing the intestine of fish contribute to their growth, digestion, nutrition, and immune function. We hypothesized that fecal samples representing the gut microbiota of rainbow trout could be associated with differential growth rates observed in fish breeding programs. If true, harnessing the functionality of this microbiota can improve the profitability of aquaculture. The first objective of this study was to test this hypothesis if gut microbiota is associated with fish growth rate (body weight). Four full-sibling families were stocked in the same tank and fed an identical diet. Two fast-growing and two slow-growing fish were selected from each family for 16S rRNA microbiota profiling. Microbiota diversity varies with different DNA extraction methods. The second objective of this study was to compare the effects of five commonly used DNA extraction methods on the microbiota profiling and to determine the most appropriate extraction method for this study. These methods were Promega-Maxwell, Phenol-chloroform, MO-BIO, Qiagen-Blood/Tissue, and Qiagen-Stool. Methods were compared according to DNA integrity, cost, feasibility and inter-sample variation based on non-metric multidimensional scaling ordination (nMDS) clusters. RESULTS:Differences in DNA extraction methods resulted in significant variation in the identification of bacteria that compose the gut microbiota. Promega-Maxwell had the lowest inter-sample variation and was therefore used for the subsequent analyses. Beta diversity of the bacterial communities showed significant variation between breeding families but not between the fast- and slow-growing fish. However, an indicator analysis determined that cellulose, amylose degrading and amino acid fermenting bacteria (Clostridium, Leptotrichia, and Peptostreptococcus) are indicator taxa of the fast-growing fish. In contrary, pathogenic bacteria (Corynebacterium and Paeniclostridium) were identified as indicator taxa for the slow-growing fish. CONCLUSION:DNA extraction methodology should be carefully considered for accurate profiling of the gut microbiota. Although the microbiota was not significantly different between the fast- and slow-growing fish groups, some bacterial taxa with functional implications were indicative of fish growth rate. Further studies are warranted to explore how bacteria are transmitted and potential usage of the indicator bacteria of fast-growing fish for development of probiotics that may improve fish health and growth.

Project description:IntroductionGrowth traits are important in poultry production, however, little is known for its regulatory mechanism at epigenetic level. Therefore, in this study, we aim to compare DNA methylation profiles between fast- and slow-growing broilers in order to identify candidate genes for chicken growth. Methylated DNA immunoprecipitation-sequencing (MeDIP-seq) was used to investigate the genome-wide DNA methylation pattern in high and low tails of Recessive White Rock (WRR(h); WRR(l)) and that of Xinhua Chickens (XH(h); XH(l)) at 7 weeks of age. The results showed that the average methylation density was the lowest in CGIs followed by promoters. Within the gene body, the methylation density of introns was higher than that of UTRs and exons. Moreover, different methylation levels were observed in different repeat types with the highest in LINE/CR1. Methylated CGIs were prominently distributed in the intergenic regions and were enriched in the size ranging 200-300 bp. In total 13,294 methylated genes were found in four samples, including 4,085 differentially methylated genes of WRR(h) Vs. WRR(l), 5,599 of XH(h) Vs. XH(l), 4,204 of WRR(h) Vs. XH(h), as well as 7,301 of WRR(l) Vs. XH(l). Moreover, 132 differentially methylated genes related to growth and metabolism were observed in both inner contrasts (WRR(h) Vs. WRR(l) and XH(h) Vs. XH(l)), whereas 129 differentially methylated genes related to growth and metabolism were found in both across-breed contrasts (WRR(h) Vs. XH(h) and WRR(l) Vs. XH(l)). Further analysis showed that overall 75 genes exhibited altered DNA methylation in all four contrasts, which included some well-known growth factors of IGF1R, FGF12, FGF14, FGF18, FGFR2, and FGFR3. In addition, we validate the MeDIP-seq results by bisulfite sequencing in some regions.ConclusionsThis study revealed the global DNA methylation pattern of chicken muscle, and identified candidate genes that potentially regulate muscle development at 7 weeks of age at methylation level.

Project description:Chicken growth traits are important in poultry production, however, little is known for its regulatory mechanism at epigenetic level. Therefore, this study aims to compare DNA methylation profiles between fast- and slow-growing broilers in order to identify candidate genes underlying chicken growth. Methylated DNA immunoprecipitation-sequencing (MeDIP-seq) was used to investigate the genome-wide DNA methylation pattern in high and low tails of Recessive White Rock (WRRh, WRRl) and that of Xinhua Chickens (XHh, XHl). The results showed that the average of methylation density was the lowest in CGIs followed by promoters. Within the gene body, the methylation density of introns was higher than UTRs and exons. Moreover, different methylation levels were observed in different repeat types with the highest in LINE/CR1. Methylated CGIs were prominently distributed in the intergenic regions and were enriched in the size range of 200-300 bp. In total 13,294 methylated genes were found in four samples, including 4,085 differentially methylated genes between WRRh and WRRl, 5,599 between XHh and XHl, 4,204 between WRRh and XHh, as well as 7,301 between WRRl and XHl. Moreover, 132 differentially methylated genes related to growth and metabolism were observed in both inner contrasts (WRRh Vs. WRRl and XHh Vs. XHl), whereas 129 differentially methylated genes related to growth and metabolism were found in both across-breed contrasts (WRRh Vs. XHh and WRRl Vs. XHl). Further analysis showed that overall 75 genes exhibited altered DNA methylation in all four contrasts, which included some well-known growth factors of IGF1R, FGF12, FGF14, FGF18, FGFR2, and FGFR3. In addition, we further validate the MeDIP-seq results by bisulfite sequencing in some regions. 12 Breast muscle samples were collected from two breeds of different growth rate, Recessive White Rock (WRR) and Xinhua Chickens (XH). Each breed included low and high-weight groups and 3 samples from each group were pooled equally for methylated DNA immunoprecipitation-sequencing (MeDIP-seq).

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Selection of fast and slow growing bacteria from fecal microbiota using continuous culture with changing dilution rate.

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