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KMID : 1812020230290020218
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Journal of Neurogastroenterology and Motility
2023 Volume.29 No. 2 p.218 ~ p.228
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Total Transit Time and Probiotic Persistence in Healthy Adults: A Pilot Study
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Annie Tremblay
Jeremie Auger
Zainab Alyousif
Sara E Caballero Calero
Olivier Mathieu
Daniela Rivero-Mendoza
Amal Elmaoui
Wendy J Dahl
Thomas A Tompkins
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Abstract
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Background/AimsMotility, stool characteristics, and microbiota composition are expected to modulate probiotics’ passage through the gut but their effects on persistence after intake cessation remain uncharacterized. This pilot, open-label study aims at characterizing probiotic fecal detection parameters (onset, persistence, and duration) and their relationship with whole gut transit time (WGTT). Correlations with fecal microbiota composition are also explored.
MethodsThirty healthy adults (30.4 ± 13.3 years) received a probiotic (30 × 109 CFU/capsule/day, 2 weeks; containing Lactobacillus helveticus R0052, Lacticaseibacillus paracasei HA-108, Bifidobacterium breve HA-129, Bifidobacterium longum R0175, and Streptococcus thermophilus HA-110). Probiotic intake was flanked by 4-week washout periods, with 18 stool collections throughout the study. WGTT was measured using 80% recovery of radio-opaque markers.
ResultsTested strains were detected in feces ~1-2 days after first intake and persistence after intake cessation was not
significantly different for R0052, HA-108, and HA-129 (~3-6 days). We identified 3 WGTT subgroups within this population (named Fast, Intermediate, and Slow), which could be classified by machine learning with high accuracy based on differentially abundant taxa. On average, R0175 persisted significantly longer in the intermediate WGTT subgroup (~8.5 days), which was mainly due to 6 of the 13 Intermediate participants for whom R0175 persisted ≥ 15 days. Machine learning classified these 13 participants according to their WGTT cluster (≥ 15 days or < 5 days) with high accuracy, highlighting differentially abundant taxa potentially associated with R0175 persistence.
ConclusionThese results support the notion that host-specific parameters such as WGTT and microbiota composition should be considered when designing studies involving probiotics, especially for the optimization of washout duration in crossover studies but also for the definition of enrollment criteria or supplementation regimen in specific populations.
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KEYWORD
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Bifidobacterium, Gastrointestinal transit, Lactobacillus, Microbiota, Probiotics
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