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Yun, Kim, Kim, Chang, Ryu, Shin, Woo, and Kim: The Effect of Probiotics, Antibiotics, and Antipyretic Analgesics on Gut Microbiota Modification
Original Article

J Bacteriol Virol 2017;47(1):64-74.

Published online: 9 February 2017

DOI: https://doi.org/10.4167/jbv.2017.47.1.64

The Effect of Probiotics, Antibiotics, and Antipyretic Analgesics on Gut Microbiota Modification

Yeojun Yun1, Han-Na Kim1, Song E Kim1, Yoosoo Chang2, Seungho Ryu2, Hocheol Shin2, So-Youn Woo3, ∗, Hyung-Lae Kim1, ∗

1Department of Biochemistry, Ewha Medical Research Institute, School of Medicine, Ewha Womans University, Seoul, Korea

2Center for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, Korea

3Department of Microbiology, Ewha Medical Research Institute, School of Medicine, Ewha Womans University, Seoul, Korea

∗Corresponding author: So-Youn Woo. Department of Microbiology, Ewha Womans University, Seoul 07985, Korea. Phone: +82-2-2650-5737, Fax: +82-2-2653-8891, e-mail: soyounwoo@ewha.ac.kr

∗Corresponding author: Hyung-Lae Kim. Department of Biochemistry, Ewha Womans University, Seoul 07985, Korea. Phone: +82-2-2650-5727, Fax: +82-2-2650-5727, e-mail: hyung@ewha.ac.kr

∗∗ This research was supported by the National Research Foundation of Korea (NRF), with funding by ICT & Future Planning (NRF-2014R1A2A2A04006291) and the Ministry of Education (NRF-2016R1A6A3A11932719). Additional support was received from the Intramural Research Support Program of Ewha Womans University School of Medicine and the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), with funding by the Ministry of Health & Welfare (HI14C0072).

Received 28 February 201714 March 2017       Accepted 22 March 2017

Copyright © 2017 Journal of Bacteriology and Virology

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Human gut microbial community is playing a critical role in human health and associated with different human disease. In parallel, probiotics, antibiotics, and antipyretic analgesics (AAs) were developed to improve human health or cure human diseases. We therefore examined how probiotics, antibiotics, and AAs influence to the gut microbiota. Three independent case/control studies were designed from the cross-sectional cohort data of 1,463 healthy Koreans. The composition of the gut microbiota in each case and control group was determined via 16S ribosomal RNA Illumina next-generation sequencing. The correlation between microbial taxa and the consumption of each drug was tested using zero-inflated Gaussian mixture models, with covariate adjustment of age, sex, and body mass index (BMI). Probiotics, antibiotics, and AAs consumption yielded the significant differences in the gut microbiota, represented the lower abundance of Megasphaera in probiotics, the higher abundance of Fusobacteria in antibiotics, and the higher abundance of Butyrivibrio and Verrucomicrobia in AAs, compared to each control group. The reduction of Erysipelotrichaceae family was common in three drugs consumption.

Keywords: Gut microbiota, Probiotics, Antibiotics, Antipyretic analgesics

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Figure 1.
Comparison of gut microbiota between 14 probiotics and 28 control groups. (A) Alpha-diversity (Shannon index), (B) beta-diversity of PCoA plots in probiotics group by weighted UniFrac, (C) weighted UniFrac distance box plot within and between groups (∗∗ p < 0.01).
jbv-47-64f1.tif
Figure 2.
Comparison of gut microbiota between 55 antibiotics and 110 control groups. (A) Alpha-diversity (Shannon index), (B) beta-diversity of PCoA plots in antibiotics group by weighted UniFrac, (C) weighted UniFrac distance box plot within and between groups (∗p < 0.05).
jbv-47-64f2.tif
Figure 3.
Comparison of gut microbiota between 47 AAs and 94 control groups. (A) Alpha-diversity (Shannon index), (B) beta-diversity of PCoA plots in AAs group by weighted UniFrac, (C) weighted UniFrac distance box plot within and between groups (∗p < 0.05).
jbv-47-64f3.tif
Table 1.
Characteristics of probiotics study population
  Probiotics Control p value
Count (male) 14 (8) 28 (16)  
Age (years) 45.93 ± 9.83 45.93 ± 9.65 1.000
BMI (kg/m2) 23.36 ± 2.75 22.30 ± 2.17 0.179
Glucose (mg/dl) 96.07 ± 11.34 94.96 ± 10.60 0.757
Triglycerides (mg/dl) 124.14 ± 84.00 106.93 ± 53.40 0.423
HDL cholesterol (mg/dl) 58.93 ± 19.44 60.29 ± 15.57 0.808
Systolic BP (mmHg) 105.87 ± 14.30 104.39 ± 11.11 0.717
Diastolic BP (mmHg) 68.86 ± 10.22 67.79 ± 9.08 0.731
HOMA-IR 1.73 ± 1.48 0.98 ± 0.54 0.089

Data are presented as mean ± standard deviation Abbreviations: BMI, body mass index; HDL, high-density lipoprotein; BP, blood pressure; HOMA-IR, homeostasis model assessment-estimated insulin resistance.

Table 2.
Characteristics of antibiotics study population
  Antibiotics Control P value
Count (male) 55 (28) 110 (56)  
Age (years) 46.58 ± 10.14 46.64 ± 9.98 0.974
BMI (kg/m2) 23.03 ± 3.22 22.67 ± 2.74 0.483
Glucose (mg/dl) 94.55 ± 10.20 95.44 ± 19.90 0.704
Triglycerides (mg/dl) 125.40 ± 105.50 104.10 ± 68.53 0.178
HDL cholesterol (mg/dl) 59.80 ± 18.36 58.73 ± 15.02 0.709
Systolic BP (mmHg) 108.22 ± 12.45 108.10 ± 14.24 0.956
Diastolic BP (mmHg) 70.64 ± 10.16 69.35 ± 9.60 0.438
HOMA-IR 1.45 ± 0.91 1.13 ± 0.77 0.027

Data are presented as mean ± standard deviation Abbreviations: BMI, body mass index; HDL, high-density lipoprotein; BP, blood pressure; HOMA-IR, homeostasis model assessment-estimated insulin resistance.

Table 3.
Characteristics of antipyretic analgesics (AAs) study population
  AAs Control P value
Count (male) 47 (23) 94 (46)  
Age (years) 43.19 ± 8.89 43.18 ± 8.82 0.995
BMI (kg/m2) 23.64 ± 3.69 23.00 ± 2.64 0.295
Glucose (mg/dl) 98.36 ± 25.74 94.53 ± 17.66 0.362
Triglycerides (mg/dl) 117.57 ± 63.46 97.03 ± 44.93 0.051
HDL cholesterol (mg/dl) 56.47 ± 14.18 59.71 ± 14.00 0.202
Systolic blood pressure (mmHg) 108.94 ± 17.34 106.15 ± 11.00 0.318
Diastolic blood pressure (mmHg) 70.81 ± 13.25 68.90 ± 8.75 0.375
HOMA-IR 1.56 ± 1.16 1.19 ± 0.90 0.061

Data are presented as mean ± standard deviation Abbreviations: BMI, body mass index; HDL, high-density lipoprotein; BP, blood pressure; HOMA-IR, homeostasis model assessment-estimated insulin resistance.

Table 4.
Significant taxa profiles of gut microbiota assessed by 16S metagenomics sequencing related with probiotics consumption
Phylum Family Genus Coeff.a p valueb
Cyanobacteria/Chloroplast     -2.37 0.017
Cyanobacteria/Chloroplast Streptophyta   -2.33 0.065
Firmicutes Erysipelotrichaceae Erysipelotrichaceae incertae sedis -3.81 0.059
Firmicutes Veillonellaceae Megasphaera -6.53 0.003

a Log2 ratio coefficient calculated by zero-inflated Gaussian mixture model using metageomeSeq package. Adjusted for age, sex, and BMI.

b Applied by Bonferroni multiple comparison correction

Table 5.
Significant taxa profiles of gut microbiota assessed by 16S metagenomics sequencing related with antibiotics consumption
Phylum Family Genus Coeff.a p valueb
Euryarchaeota (Archaea)     -2.97 6.04E-08
Euryarchaeota (Archaea) Methanobacteriaceae   -3.65 1.51E-10
Euryarchaeota (Archaea) Methanobacteriaceae Methanobrevibacter -3.30 4.33E-09
Bacterodetes Porphyromonadaceae Butyricimonas -1.70 5.59E-04
Firmicutes Paenibacillaceae   -2.85 8.06E-12
Firmicutes Paenibacillaceae Paenibacillus -2.85 1.11E-11
Firmicutes Christensenellaceae   -1.83 8.78E-06
Firmicutes Christensenellaceae Christensenella -1.77 3.71E-05
Firmicutes Vallitalea   -1.59 0.01
Firmicutes Enterococcaceae   -1.56 0.003
Firmicutes Enterococcaceae Enterococcus -1.61 0.005
Firmicutes Acidaminococcaceae Acidaminococcus -1.75 0.025
Firmicutes Erysipelotrichaceae Erysipelotrichaceae incertae sedis -4.51 3.28E-17
Firmicutes Erysipelotrichaceae Erysipelothrix -4.07 1.17E-16
Firmicutes Lachnospiraceae Butyrivibrio -3.24 8.28E-08
Firmicutes Ruminococcaceae Fastidiosipila -1.55 1.97E-06
Firmicutes Ruminococcaceae Anaerotruncus -0.93 0.027
Firmicutes Veillonellaceae Megasphaera -2.50 9.54E-05
Fusobacteria     1.98 0.007

a Log2 ratio coefficient calculated by zero-inflated Gaussian mixture model using metageomeSeq package. Adjusted for age,sex, and BMI.

b Applied by Bonferroni multiple comparison correction

Table 6.
Significant taxa profiles of gut microbiota assessed by 16S metagenomics sequencing related with AAs consumption
Phylum Family Genus Coeff.a p valueb
Euryarchaeota (Archaea)     3.10 3.34E-05
Verrucomicrobia     1.57 0.015
Firmicutes Clostridiaceae   1.77 0.026
Bacterodetes Porphyromonadaceae Butyricimonas -2.41 2.54E-08
Firmicutes Lachnospiraceae Butyrivibrio 4.84 1.60E-06
Firmicutes Erysipelotrichaceae Erysipelotrichaceae incertae sedis -3.36 1.70E-06
Proteobacteria Desulfovibrionaceae Desulfovibrio 2.57 6.14E-06

a Log2 ratio coefficient calculated by zero-inflated Gaussian mixture model using metageomeSeq package. Adjusted for age, sex, and BMI.

b Applied by Bonferroni multiple comparison correction

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