Effect of sublethal concentrations of bactericidal antibiotics on mutation frequency and stress response of Listeria monocytogenes

Antibacterial effect and mechanism of theaflavin against Listeria monocytogenes and its application on apple skins

Theaflavin 3,3'-digallate (TF3), a major polyphenolic component of black tea, exhibits antibacterial effects against many foodborne pathogens. However, the antibacterial mechanisms of TF3 against Listeria monocytogenes remain unclear. In this study, we investigated the effects of TF3 on viability, biofilm, and membrane function of L. monocytogenes by the conventional plating method, crystal violet staining, and microscopy using fluorescent dyes JC-1 and Laurdan, respectively. It was found that TF3 showed excellent antibacterial activity against L. monocytogenes with the minimum inhibitory concentration of 62.5 mg/L. The viable count determined on TSA decreased by 3 log after the treatment for 2 h with TF3 at 62.5 mg/L. The viable count determined on TSA containing 4% NaCl decreased by more than 4 log after the treatment for 30 min with TF3 at the same concentration, suggesting that TF3 gave damage on the cells, enhancing the antibacterial action of 4% NaCl, but the damage was recoverable in the absence of 4% NaCl. To explore the antibacterial mechanisms of TF3, the effects of TF3 on membrane potential and membrane fluidity were investigated. TF3 reduced both membrane potential and fluidity of L. monocytogenes at 62.5 mg/L, suggesting that TF3 damaged the structural integrity of the cell membrane. TF3 reduced biofilm mass of mature biofilm of L. monocytogenes. Moreover, THEAFLAVIN TF40, a commercially available Camellia sinensis leaf extract containing TF3, reduced viable count of L. monocytogenes by 2 log on apple skin. These results suggest the potential of theaflavins as a natural anti-Listeria disinfectant.

Metabolomics analysis of the lactobacillus plantarum ATCC 14917 response to antibiotic stress

BACKGROUND

Lactobacillus plantarum has been found to play a significant role in maintaining the balance of intestinal flora in the human gut. However, it is sensitive to commonly used antibiotics and is often incidentally killed during treatment. We attempted to identify a means to protect L. plantarum ATCC14917 from the metabolic changes caused by two commonly used antibiotics, ampicillin, and doxycycline. We examined the metabolic changes under ampicillin and doxycycline treatment and assessed the protective effects of adding key exogenous metabolites.

RESULTS

Using metabolomics, we found that under the stress of ampicillin or doxycycline, L. plantarum ATCC14917 exhibited reduced metabolic activity, with purine metabolism a key metabolic pathway involved in this change. We then screened the key biomarkers in this metabolic pathway, guanine and adenosine diphosphate (ADP). The exogenous addition of each of these two metabolites significantly reduced the lethality of ampicillin and doxycycline on L. plantarum ATCC14917. Because purine metabolism is closely related to the production of reactive oxygen species (ROS), the results showed that the addition of guanine or ADP reduced intracellular ROS levels in L. plantarum ATCC14917. Moreover, the killing effects of ampicillin and doxycycline on L. plantarum ATCC14917 were restored by the addition of a ROS accelerator in the presence of guanine or ADP.

CONCLUSIONS

The metabolic changes of L. plantarum ATCC14917 under antibiotic treatments were determined. Moreover, the metabolome information that was elucidated can be used to help L. plantarum cope with adverse stress, which will help probiotics become less vulnerable to antibiotics during clinical treatment.

Understanding the effects of sub-inhibitory antibiotic concentrations on the development of β-lactamase resistance based on quantile regression analysis

AIMS

Quantile regression is an alternate type of regression analysis that has been shown to have numerous advantages over standard linear regression. Unlike linear regression, which uses the mean to fit a linear model, quantile regression uses a data set's quantiles (or percentiles), which leads to a more comprehensive analysis of the data. However, while relatively common in other scientific fields such as economic and environmental modeling, it is infrequently used to understand biological and microbiological systems.

METHODS AND RESULTS

We analyzed a set of bacterial growth rates using quantile regression analysis to better understand the effects of antibiotics on bacterial fitness. Using a bacterial model system containing 16 variant genotypes of the TEM β-lactamase enzyme, we compared our quantile regression analysis to a previously published study that uses the Tukey's range test, or Tukey honestly significantly difference (HSD) test. We find that trends in the distribution of bacterial growth rate data, as viewed through the lens of quantile regression, can distinguish between novel genotypes and ones that have been clinically isolated from patients. Quantile regression also identified certain combinations of genotypes and antibiotics that resulted in bacterial populations growing faster as the antibiotic concentration increased-the opposite of what was expected. These analyses can provide new insights into the relationships between enzymatic efficacy and antibiotic concentration.

CONCLUSIONS

Quantile regression analysis enhances our understanding of the impacts of sublethal antibiotic concentrations on enzymatic (TEM β-lactamase) efficacy and bacterial fitness. We illustrate that quantile regression analysis can link patterns in growth rates with clinically relevant mutations and provides an understanding of how increasing sub-lethal antibiotic concentrations, like those found in our modern environment, can affect bacterial growth rates, and provide insight into the genetic basis for varied resistance.

Control of Listeria monocytogenes in food industry by a combination treatment of natural aromatic compound with Listeria-specific bacteriophage cocktail

Most Listeria monocytogenes found in the food industry are listeriosis-causing pathogens and possess the ability to form biofilms on food and food contact materials (FCMs). This study aims to evaluate the efficacy of the combination treatment of natural aromatic compounds (thymol, eugenol, carvacrol, and citral) with a Listeria-specific phage cocktail in mitigating the threat posed by L. monocytogenes in the food industry. In vitro combination treatment of 1 minimal inhibitory concentration (MIC) of natural aromatic compound with phage cocktail at multiplicity of infection (MOI) 100 reduced more than 4 log CFU/mL of L. monocytogenes planktonic cells and inhibited biofilm formation. In addition, the expression of virulence-related genes (flaA, motB, hlyA, prfA, and actA) and the stress response (sigB) gene were significantly downregulated. The combination of natural aromatic compound with phage cocktail reduced the biofilm cell population on contaminated celery by more than 2 log CFU/g and by more than 2 log CFU/cm2 on already-formed biofilm on FCMs, but it was less effective on chicken meat, with an approximate reduction of only 1 log CFU/g. The antibiofilm activity toward preformed L. monocytogenes biofilms was also observed using field-emission scanning electron microscopy (FESEM) and confocal laser scanning microscopy (CLSM). COMSTAT analysis of the structural change of biofilms revealed that major biofilm structure parameters (biovolume, thickness, diffusion distance, and microcolonies at substratum) were reduced after treatment. Our findings suggest that the combination of natural aromatic compounds with a phage cocktail has enormous potential as an antimicrobial and antibiofilm agent for controlling L. monocytogenes in the food industry.

Lactic acid bacteria secreted proteins as potential Listeria monocytogenes quorum sensing inhibitors

Listeria monocytogenes is an important human and animal pathogen able to cause an infection named listeriosis and is mainly transmitted through contaminated food. Among its virulence traits, the ability to form biofilms and to survive in harsh environments stand out and lead to the persistence of L. monocytogenes for long periods in food processing environments. Virulence and biofilm formation are phenotypes regulated by quorum sensing (QS) and, therefore, the control of L. monocytogenes through an anti-QS strategy is promising. This study aimed to identify, by in silico approaches, proteins secreted by lactic acid bacteria (LAB) potentially able to interfere with the agr QS system of L. monocytogenes. The genome mining of Lacticaseibacillus rhamnosus GG and Lactobacillus acidophilus NCFM revealed 151 predicted secreted proteins. Concomitantly, the three-dimensional (3D) structures of AgrB and AgrC proteins of L. monocytogenes were modeled and validated, and their active sites were predicted. Through protein-protein docking and molecular dynamic, Serine-type D-Ala-D-Ala carboxypeptidase and L,D-transpeptidase, potentially secreted by L. rhamnosus GG and L. acidophilus NCFM, respectively, were identified with high affinity to AgrB and AgrC proteins, respectively. By inhibiting the translocation of the cyclic autoinducer peptide (cyclic AIP) via AgrB, and its recognition in the active site of AgrC, these LAB proteins could disrupt L. monocytogenes communication by impairing the agr QS system. The application of the QS inhibitors predicted in this study can emerge as a promising strategy in controlling L. monocytogenes in food processing environment and as an adjunct to antibiotic therapy for the treatment of listeriosis.