Habitual dietary intake of monozygotic twins associated with fecal microbiota composition

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The establishment of microbial populations in the gastrointestinal (GI)-tract is a complex process, involving microbial and host interactions eventually resulting in a dense and stable population. Recently, the identification of microbial species from fecal samples has become more accurate with the use of 16S RNA gene-based methods. However, although these molecular-based detection methods have apparent benefits over culture-based techniques, they involve potential pitfalls that should be taken into consideration when studying the fecal microbiota, such as the storage conditions and deoxyribonucleic acid (DNA)-extraction. Therefore, the effects of different storage conditions and DNA-extraction protocols on fecal samples were evaluated in this study. Whereas the DNA-extraction protocol did not affect the numbers of Bacteroides spp., the abundance of this group showed a significant decrease after one week's storage at -20°C. Furthermore, the numbers of predominant bacteria, Eubacterium rectale group, Clostridium leptum group, bifidobacteria and Atopobium group, were significantly higher in samples stored at -70°C after mechanical DNA-extraction than after enzymatic DNA-extraction as detected with real-time PCR (qPCR). These results indicate that rigorous mechanical lysis leads to the detection of higher bacterial numbers from human fecal samples than enzymatic DNA-extraction. Therefore, the use of different DNA-extraction protocols may partly explain contradictory results reported in previous studies.

The composition of the human intestinal microbiota is influenced by host-specific factors such as age, genetics and physical and chemical conditions encountered in the GI-tract. On the other hand, it is modulated by environmental factors with impact on the host during the lifespan, such as diet. The impact of diet on the gut microbiota has usually been assessed by subjecting people to the same controlled diet, and thereafter following the shifts in the microbiota. In the present study, the habitual dietary intake of monozygotic twins was associated with the fecal microbiota composition, which was analysed using qPCR and Denaturing Gradient Gel Electrophoresis (DGGE). The effect of diet on the numbers of the bacteria was described using a hierarchical linear mixed model that included the twin individuals, stratified by body mass index, and their families as random effects. The abundance and diversity of the bacterial groups studied did not differ between normal weight, overweight, and obese individuals with the techniques used. However, intakes of energy, monounsaturated fat, (n-3) polyunsaturated fat, (n-6) polyunsaturated fat and soluble fibre had significant associations with the fecal bacterial numbers. In addition, co-twins with identical energy intakes had more similar numbers and DGGE-profile diversities of Bacteroides spp. than co-twins with different intakes. Moreover, co-twins who ingested the same amounts of saturated fat had very similar DGGE-profiles of Bacteroides spp., whereas co-twins with similar consumption of fibre had very low bifidobacterial DGGE-profile similarity.

Thereafter, the impact of the energy intake on the fecal microbiota of a group of 16 obese individuals was assessed during a 12 month intervention, which consisted of a 6 week very low energy diet (VLED) and thereafter a follow-up period of 5, 8 and 12 months. The diet plan was combined with exercise and lifestyle counselling. Fecal samples were analyzed using qPCR, DGGE and fluorescent in situ hybridization. The effect of the energy restricted diet on the fecal bacterial numbers was described using a linear mixed model that accounted for repeated measurements in the same individual. The VLED period affected the major fecal microbial groups; in particular bifidobacteria decreased compared to the baseline numbers. Furthermore, the change in numbers of the fecal bacterial groups studied, with the exception of Bacteroides spp., followed the energy intake and not the weight changes during the 12 months. Methanogens were detected in 56% of the participants at every sampling time point, regardless of the change in energetic intake. In addition, the relationships between the major fecal microbial groups and weight loss, change in fat mass, and change in lean mass were also evaluated. Weight loss was associated with a decrease in Lactobacillus group bacteria, whereas lean mass loss was associated with decreases in both bifidobacteria and Lactobacillus group bacteria. These findings confirm that the diet and energetic intake play an important role in modulation of the fecal microbiota.

Finally, the potential of utilising the information on expression levels of selected stress genes in assessing the quality of probiotic products was evaluated. For this purpose, reverse transcription (RT)-qPCR methods were developed to study the expression of clpL1 and clpL2 stress genes in Lactobacillus rhamnosus VTT E-97800 cells after exposure to processing-related stress conditions or to freeze-drying. Heat treatments were performed with L. rhamnosus VTT E-97800 in laboratory scale, whereas acid treatments were performed both in laboratory and fermenter scale. RNA was extracted from fresh cells and freeze-dried powders. clpL1 and clpL2 transcripts were analysed by RT-qPCR using SYBR Green I. clpL1 was induced in L. rhamnosus VTT E-97800 cells exposed to 50°C and to a much lesser extent in cells exposed to 47°C. No induction was observed for clpL2 during either acid or heat treatment in any of the conditions applied. RNA isolation from freeze-dried powders was unsuccessful, although several attempts were made with high quality products. These results suggest that developing quality indicators for probiotic products based on differences in the expression of stress genes will be a challenging task, since rather harsh conditions are apparently needed to detect differences in the gene expression. In addition, the unsuccessful RNA isolation from freeze-dried powders hampers the applicability of this technique in the quality control of probiotic products.

Source: http://www.vtt.fi


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