Probiotic Supplementation and Marathon Runners: there are any effect up to Gut Microbiota and neutrophil function?

Probiotic supplementation can induce positive alterations in intestinal environment, however the effect of a month period short of probiotic supplementation on gut microbiota and neutrophil function of endurance athletes is not known. PURPOSE: Investigate the effect of thirty days of probiotic supplementation up on gut microbiota composition and neutrophil function in marathon athletes. METHODS: Twenty-seven marathon runners were double-blind randomly assigned to either a Probiotic (PR) (35,96 ± 5,81 years,79,30 ±10,99Kg) or Placebo (PL) group (PL= 40,46 ± 7,79 years, 72,67 ±10,20Kg). PR consumed Lactobacillus Acidophilus and Bifidobacterium Lactis (10x109UFC + maltodextrin) during 30 days in a sachet form, while PL received a sachet with maltodextrin (5g/day). The gut microbiota composition was evaluated before (BASELINE) and after the supplementation period (POS-SUP). Fiber consumption was evaluated using one-day diet record at the baseline and Pos-sup. Blood collection was realized (BASELINE and POS-SUP) to verify neutrophil function, after blood cell neutrophil isolation peroxide and cytokine production (IL-1- β; TNF-α; IL-6; IL-8) was analyzed. The Bacterial DNA were extracted using QIAamp Fast DNA Stool Mini Kit® and faecal microbiota composition was assessed by 16S rRNA sequencing, V3-V4 regions, with Illumina® MiiSeq plataform. Operational taxonomic units (OTUs) and diversity indices were obtained after bioinformatic treatment on Qiime2® software. β-diversity was computed considering the sampling of 1,800 sequences per sample, which was based on the rarefaction curve. To test differences among groups and time, it was performed a pairwise PERMANOVA for beta-diversity and ANCOM for OTUs relative abundance. Data analyses were conducted using SAS Statistical Software version 9.3® (p< 0.05 and multiple tests corrected when necessary). For neutrophil function was used the of repeated measures statistical test mixed Model (with ‘group’ and ‘time’ as factors) being used with Tukey’s post hoc – GraphPad

Prim8 ®. RESULTS: Fiber consumption was similar between groups with no statistical difference [BASELINE: 23,65 ± 10,53 (PL); 24,92± 19,15 (PR); POS-SUP= 25,63± 15,61 (PL); 15,61±15,25(PR)]. The peroxide and cytokines production by neutrophils were no different between groups. From the gut microbiota analyses, it was identified 2.634 OTUs based on 173.096 final sequences. Regarding beta- diversity, UniFrac weighted index was different between groups (p=0,04; PERMANOVA) and the relative abundance of Lactobacillus ruminis was significant different between groups, in which PR exhibited significant high levels after supplementation period. DISCUSSION: Probiotic induced changes in the intestinal environment or increased interaction among specific bacterial species leading to an increase in the relative abundance of lactic acid bacteria, such as Lactobacillus ruminis. This effect seems to be a