Controlling Listeria monocytogenes Growth and Biofilm Formation Using Flavonoids.

ABSTRACT: The aim of this study was to investigate the ability of natural plant-derivate products (flavonoid compounds) to inhibit the growth and biofilm-forming ability of Listeria monocytogenes. A collection of 500 synthetic and natural flavonoids were tested individually on strains of L. monocytogenes for their antimicrobial and antibiofilm activity. The flavonoids were tested against a L. monocytogenes cocktail of five strains at a concentration of 100 µM to determine their effect on planktonic growth. The optical density was measured every hour for 24 h at 37°C, and every hour for 48 h at 22°C. A total of 17 flavonoids were chosen for further study because of their ability to significantly reduce the growth of L. monocytogenes up to 97%. An additional two flavonoids that increased planktonic growth were chosen as well to investigate whether they had the same effect on biofilm growth. A lower concentration of flavonoid compounds (50 µM) was selected to investigate the individual effects on L. monocytogenes biofilm formation using (i) stainless steel coupons to quantify biomass using crystal violet staining and (ii) glass slides using confocal laser scanning microscopic (CLSM) imaging to observe the biofilm architecture. The 19 flavonoids showed various levels of L. monocytogenes biofilm growth inhibition, ranging from 2 to 100% after 48 h of incubation at 22 or 10°C. This includes 18 of the 19 flavonoids significantly (P ≤ 0.05) inhibiting L. monocytogenes biofilm formation on stainless steel coupons under at least one of the testing conditions. However, only one flavonoid compound demonstrated significant biofilm inhibition (P ≤ 0.05) under all conditions tested. Furthermore, 8 of the selected 19 flavonoid compounds showed visible reductions through CLSM in L. monocytogenes biofilm formation. Overall, we identified five flavonoid compounds to be promising antibiofilm and antimicrobial agents against L. monocytogenes.

Metagenomics-Based, Strain-Level Analysis of Escherichia coli From a Time-Series of Microbiome Samples From a Crohn's Disease Patient.

Dysbiosis of the gut microbiome, including elevated abundance of putative leading bacterial triggers such as E. coli in inflammatory bowel disease (IBD) patients, is of great interest. To date, most E. coli studies in IBD patients are focused on clinical isolates, overlooking their relative abundances and turnover over time. Metagenomics-based studies, on the other hand, are less focused on strain-level investigations. Here, using recently developed bioinformatic tools, we analyzed the abundance and properties of specific E. coli strains in a Crohns disease (CD) patient longitudinally, while also considering the composition of the entire community over time. In this report, we conducted a pilot study on metagenomic-based, strain-level analysis of a time-series of E. coli strains in a left-sided CD patient, who exhibited sustained levels of E. coli greater than 100X healthy controls. We: (1) mapped out the composition of the gut microbiome over time, particularly the presence of E. coli strains, and found that the abundance and dominance of specific E. coli strains in the community varied over time; (2) performed strain-level de novo assemblies of seven dominant E. coli strains, and illustrated disparity between these strains in both phylogenetic origin and genomic content; (3) observed that strain ST1 (recovered during peak inflammation) is highly similar to known pathogenic AIEC strains NC101 and LF82 in both virulence factors and metabolic functions, while other strains (ST2-ST7) that were collected during more stable states displayed diverse characteristics; (4) isolated, sequenced, experimentally characterized ST1, and confirmed the accuracy of the de novo assembly; and (5) assessed growth capability of ST1 with a newly reconstructed genome-scale metabolic model of the strain, and showed its potential to use substrates found abundantly in the human gut to outcompete other microbes. In conclusion, inflammation status (assessed by the blood C-reactive protein and stool calprotectin) is likely correlated with the abundance of a subgroup of E. coli strains with specific traits. Therefore, strain-level time-series analysis of dominant E. coli strains in a CD patient is highly informative, and motivates a study of a larger cohort of IBD patients.