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

## TL;DR

This study shows that the gut microbiome composition of older adults can predict whether they will respond to probiotic interventions.

## Contribution

The study identifies specific gut microbiome patterns that differentiate responders and non-responders to probiotics in geriatrics.

## Key findings

- Genera like Lactobacillus and Clostridium in Firmicutes differ significantly between responders and non-responders.
- Proteobacteria genera such as Escherichia and Shigella also show significant differences between groups.
- Microbial biomarkers were identified that correlate with a positive response to probiotic intervention.

## Abstract

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.

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).

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.