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Geriatric Respondents and Non-Respondents to Probiotic Intervention Can be Differentiated by Inherent Gut Microbiome Composition.

Senan S, Prajapati JB, Joshi CG, Sreeja V, Gohel MK, Trivedi S, Patel RM, Pandya H, Singh US, Phatak A, Patel HA - Front Microbiol (2015)

Bottom Line: Among respondents and non-respondents, the chief genera of phylum Firmicutes that showed significant differences are Lactobacillus, Clostridium, Eubacterium, and Blautia (q < 0.002), while in the genera of phylum Proteobacteria included Shigella, Escherichia, Burkholderia and Camphylobacter (q < 0.002).We have identified potential microbial biomarkers and taxonomic patterns that correlate with a positive response to probiotic intervention in geriatric volunteers.Future work with larger cohorts of geriatrics with diverse dietary influences could reveal the potential of the signature patterns of microbiota for personalized nutrition.

View Article: PubMed Central - PubMed

Affiliation: Department of Dairy Science, South Dakota State University , Brookings, SD , USA.

ABSTRACT

Scope: Probiotic interventions are known to have been shown to influence the composition of the intestinal microbiota in geriatrics. The growing concern is the apparent variation in response to identical strain dosage among human volunteers. One factor that governs this variation is the host gut microbiome. In this study, we attempted to define a core gut metagenome, which could act as a predisposition signature marker of inherent bacterial community that can help predict the success of a probiotic intervention.

Methods and results: To characterize the geriatric gut microbiome, we designed primers targeting the 16S rRNA hypervariable region V2-V3 followed by semiconductor sequencing using Ion Torrent PGM. Among respondents and non-respondents, the chief genera of phylum Firmicutes that showed significant differences are Lactobacillus, Clostridium, Eubacterium, and Blautia (q < 0.002), while in the genera of phylum Proteobacteria included Shigella, Escherichia, Burkholderia and Camphylobacter (q < 0.002).

Conclusion: We have identified potential microbial biomarkers and taxonomic patterns that correlate with a positive response to probiotic intervention in geriatric volunteers. Future work with larger cohorts of geriatrics with diverse dietary influences could reveal the potential of the signature patterns of microbiota for personalized nutrition.

No MeSH data available.


Related in: MedlinePlus

Estimation of the phylogenetic diversity of the gut microbiota in the respondent and non-respondent groups using the (A) Shannon index, (B) phylogenetic distance, (C) Chao1, and (D) observed species. The values are means, and error bars indicate the 95% confidence intervals.
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Figure 3: Estimation of the phylogenetic diversity of the gut microbiota in the respondent and non-respondent groups using the (A) Shannon index, (B) phylogenetic distance, (C) Chao1, and (D) observed species. The values are means, and error bars indicate the 95% confidence intervals.

Mentions: The alpha diversity of the respondent group before probiotic feeding (30.8 ± 4.8) and after feeding (26.6 ± 3.6) was higher than non-respondents’ measures for before (25.6 ± 4.5) and after probiotic feeding (24.6 ± 5.8). This indicates that bacterial richness is a factor that promotes responsiveness toward beneficial strains in the gut. To investigate differences in rarefaction measures, we rarified each sample at 33,000 reads and performed the two-sample t-test on the two groups. Respondents had significantly greater alpha diversity indices like phylogenetic distance (p = 0.022), Chao1 (p = 0.019), and Shannon index (p = 0.00058) than the non-respondents (Figure 3). A non-significant increase in observed species in case of non-respondents (p = 0.27) could be due to presence of distinct commensals that reflect the host’s dietary and geographical differences. There was a non-significant abundance of Clostridium, Shigella, and Listeria among rural respondents. Poor sanitation and hygiene maintained in the rural households could have led to the distinct differences in gut microbiota.


Geriatric Respondents and Non-Respondents to Probiotic Intervention Can be Differentiated by Inherent Gut Microbiome Composition.

Senan S, Prajapati JB, Joshi CG, Sreeja V, Gohel MK, Trivedi S, Patel RM, Pandya H, Singh US, Phatak A, Patel HA - Front Microbiol (2015)

Estimation of the phylogenetic diversity of the gut microbiota in the respondent and non-respondent groups using the (A) Shannon index, (B) phylogenetic distance, (C) Chao1, and (D) observed species. The values are means, and error bars indicate the 95% confidence intervals.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4561823&req=5

Figure 3: Estimation of the phylogenetic diversity of the gut microbiota in the respondent and non-respondent groups using the (A) Shannon index, (B) phylogenetic distance, (C) Chao1, and (D) observed species. The values are means, and error bars indicate the 95% confidence intervals.
Mentions: The alpha diversity of the respondent group before probiotic feeding (30.8 ± 4.8) and after feeding (26.6 ± 3.6) was higher than non-respondents’ measures for before (25.6 ± 4.5) and after probiotic feeding (24.6 ± 5.8). This indicates that bacterial richness is a factor that promotes responsiveness toward beneficial strains in the gut. To investigate differences in rarefaction measures, we rarified each sample at 33,000 reads and performed the two-sample t-test on the two groups. Respondents had significantly greater alpha diversity indices like phylogenetic distance (p = 0.022), Chao1 (p = 0.019), and Shannon index (p = 0.00058) than the non-respondents (Figure 3). A non-significant increase in observed species in case of non-respondents (p = 0.27) could be due to presence of distinct commensals that reflect the host’s dietary and geographical differences. There was a non-significant abundance of Clostridium, Shigella, and Listeria among rural respondents. Poor sanitation and hygiene maintained in the rural households could have led to the distinct differences in gut microbiota.

Bottom Line: Among respondents and non-respondents, the chief genera of phylum Firmicutes that showed significant differences are Lactobacillus, Clostridium, Eubacterium, and Blautia (q < 0.002), while in the genera of phylum Proteobacteria included Shigella, Escherichia, Burkholderia and Camphylobacter (q < 0.002).We have identified potential microbial biomarkers and taxonomic patterns that correlate with a positive response to probiotic intervention in geriatric volunteers.Future work with larger cohorts of geriatrics with diverse dietary influences could reveal the potential of the signature patterns of microbiota for personalized nutrition.

View Article: PubMed Central - PubMed

Affiliation: Department of Dairy Science, South Dakota State University , Brookings, SD , USA.

ABSTRACT

Scope: Probiotic interventions are known to have been shown to influence the composition of the intestinal microbiota in geriatrics. The growing concern is the apparent variation in response to identical strain dosage among human volunteers. One factor that governs this variation is the host gut microbiome. In this study, we attempted to define a core gut metagenome, which could act as a predisposition signature marker of inherent bacterial community that can help predict the success of a probiotic intervention.

Methods and results: To characterize the geriatric gut microbiome, we designed primers targeting the 16S rRNA hypervariable region V2-V3 followed by semiconductor sequencing using Ion Torrent PGM. Among respondents and non-respondents, the chief genera of phylum Firmicutes that showed significant differences are Lactobacillus, Clostridium, Eubacterium, and Blautia (q < 0.002), while in the genera of phylum Proteobacteria included Shigella, Escherichia, Burkholderia and Camphylobacter (q < 0.002).

Conclusion: We have identified potential microbial biomarkers and taxonomic patterns that correlate with a positive response to probiotic intervention in geriatric volunteers. Future work with larger cohorts of geriatrics with diverse dietary influences could reveal the potential of the signature patterns of microbiota for personalized nutrition.

No MeSH data available.


Related in: MedlinePlus