Folia Microbiologica

, Volume 64, Issue 4, pp 497–508 | Cite as

Human gut microbes are susceptible to antimicrobial food additives in vitro

  • Lucia Hrncirova
  • Tomas Hudcovic
  • Eliska Sukova
  • Vladimira Machova
  • Eva Trckova
  • Jan Krejsek
  • Tomas HrncirEmail author
Original Article


The aim of this work was to test the hypothesis that antimicrobial food additives may alter the composition of human gut microbiota by selectively suppressing the growth of susceptible gut microbes. To explore the influence of antimicrobial food additives on the composition of the human gut microbiota, we examined the susceptibility of both aerobic and anaerobic gut bacteria to sodium benzoate, sodium nitrite, and potassium sorbate, and their combinations, using a broth microdilution method. The tested bacteria exhibited a wide range of susceptibilities to food additives. For example, the most susceptible strain, Bacteroides coprocola, was almost 580 times more susceptible to sodium nitrite than the most resistant strain, Enterococcus faecalis. However, most importantly, we found that gut microbes with known anti-inflammatory properties, such as Clostridium tyrobutyricum or Lactobacillus paracasei, were significantly more susceptible to additives than microbes with known proinflammatory or colitogenic properties, such as Bacteroides thetaiotaomicron or Enterococcus faecalis. Our data show that some human gut microbes are highly susceptible to antimicrobial food additives. We speculate that permanent exposure of human gut microbiota to even low levels of additives may modify the composition and function of gut microbiota and thus influence the host’s immune system. Whether the effect of additive-modified gut microbiota on the human immune system could explain, at least in part, the increasing incidence of allergies and autoimmune diseases remains to be shown.


Gut microbiota Autoimmune diseases Dysbiosis Mucosal immunology Food additives Chou-Talalay method 



We would like to thank Radka Stribrna and Jarmila Jarkovska for their invaluable technical support and James Rizzo for editing and proofreading the manuscript.

Funding information

This study was supported by the Charles University Grant Agency (No. 906613), the Czech Science Foundation (15-09518S, 15-07268S, 17-07332S, and 17-31248A), and Institutional Research Concept (RVO: 61388971). This work was also supported by Charles University in Prague, Faculty of Medicine in Hradec Kralove, Czech Republic, project “PRVOUK” P37/10.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

The study was reviewed and approved by the Institutional Review Committee (protocol no. PP77-2014), and all subjects participating in the study signed and dated Informed Consent and Fecal Donor Agreement forms.

Supplementary material

12223_2018_674_MOESM1_ESM.xlsx (14 kb)
Table S1 The statistical evaluation of interstrain differences in susceptibility to additives. For each single additive and its combination, the different pairs of IC50 means, averaged from three independent experiments, were compared using ordinary one-way ANOVA followed by Tukey’s multiple comparisons test. The table reports p-values adjusted to account for multiple comparisons and asterisks summarizing statistical significance (p < 0.0001 (****), p < 0.001 (***), p < 0.01 (**), p < 0.05 (*), p ≥ 0.05 (ns)). (XLSX 14 kb)
12223_2018_674_MOESM2_ESM.xlsx (14 kb)
Table S2 The statistical evaluation of the antibacterial potency of additives. The potency of additives was analyzed by comparing various IC50 means, averaged from all eight bacterial strains for each additive, against the IC50 mean of the most potent additive, sodium nitrite. The statistical significance was evaluated using two-way ANOVA followed by Dunnett’s multiple comparisons test. The table reports p-values adjusted to account for multiple comparisons and asterisks summarizing statistical significance (p < 0.0001 (****), p < 0.001 (***), p < 0.01 (**), p < 0.05 (*), p ≥ 0.05 (ns)). (XLSX 14 kb)
12223_2018_674_Fig5_ESM.png (220 kb)
Fig. S1

The dose-effect linear plots show the growth inhibition effects of each additive alone and its combinations. The growth inhibition effect is shown as a fractional response of bacteria to additives. The fraction affected (Fa) was calculated by the following formula: Fa = 1 - (% growth/100). The Fa ranges from 0 to 1, with the Fa value of 0 meaning no growth inhibition and the value of 1 representing 100% growth inhibition. Symbols represent the mean value ± SD from at least three independent experiments. (PNG 220 kb)

12223_2018_674_MOESM3_ESM.eps (1.2 mb)
High Resolution Image (EPS 1215 kb)
12223_2018_674_Fig6_ESM.png (201 kb)
Fig. S2

Polygonograms (at 50% growth inhibition (Fa = 0.5)) for sodium benzoate, sodium nitrite, and potassium sorbate. The solid green line represents synergism (CI < 0.9), the broken thin black line represents additive effects (CI = 0.9–1.1), and the broken red line represents antagonism (CI > 1.1). The specific CI values of all binary AMFA combinations are shown next to the lines. The thickness of the line represents the strength of synergism or antagonism. The CI values were calculated using CompuSyn software and graphs were drawn using Affinity Design software BEN, sodium benzoate; NIT, sodium nitrite; SOR, potassium sorbate; CI, combination index; Fa, fraction affected (PNG 201 kb)

12223_2018_674_MOESM4_ESM.eps (795 kb)
High Resolution Image (EPS 795 kb)


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Copyright information

© Institute of Microbiology, Academy of Sciences of the Czech Republic, v.v.i. 2019

Authors and Affiliations

  1. 1.The Faculty of Medicine in Hradec KraloveCharles UniversityHradec KraloveCzech Republic
  2. 2.The Institute of MicrobiologyThe Czech Academy of SciencesNovy HradekCzech Republic

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