Finding shared kitchen microbiota across European households

Humans are constantly exposed to a variety of microorganisms, which can have both positive and adverse health effects. Significant exposure to these microbes occurs indoors, with high bacterial colonization reported in the kitchen. To date, no study has compared the microbial communities in homes across countries, which is essential to determine whether there is a dominant kitchen microbiota.

Research: Mapping the kitchen microbiota in five European countries reveals a set of key bacteria across the country, cleaning kitchen surfaces and utensils. Image credit: Africa Studio / Shutterstock.com

About the study

A recent study published in the journal Applied and Environmental Microbiology Mapped the microbiota on kitchen surfaces and cleaning utensils to determine associations between microbiota, household products, and country.

Kitchen surface and cleaning utensil samples were collected from 74 households in Hungary, France, Portugal, Romania and Norway. Surface samples were obtained from different kitchen items prior to dinner preparation.

Sponges and cloth cleaning samples were obtained after food preparation and then subjected to deoxyribonucleic acid (DNA) extraction and 16S ribosomal ribonucleic acid (rRNA) gene sequencing. Alpha diversity was analyzed using the Shannon index, observed features and phylogenetic diversity of confidence.

Linear mixed models were used to test alpha diversity differences across sample types and countries. Beta heterogeneity was analyzed by unweighted and weighted UniFrock, Jacquard and Bray-Curtis. Univariate and multivariate analyzes examined differences between sample districts and categories.

Study results

A total of 305 samples were analyzed and 3,487 sub-functional taxonomic units (sOTUs) were identified from over 18.8 million sequences. An average of 61,960 sequences were obtained for each sample, with 5,420 sequences isolated for each sOTU.

The kitchen microbiota consisted of members of 793 species belonging to 297 families. From the most frequent rows Proteobacteria Phylum, continued Companies, Bacteriota, And Actinobacteria Bylaw

There were too many species and families Acinetobacter, Pseudomonas, Anhydrobacter, Enterobacteriaceae, And Yersinaceae. Forty-five sOTUs were identified in Acinetobacter Kindred, with A. johnsonii Being very frequent Acinetobacter species.

Sixty-four sOTUs were represented Pseudomonas race Nineteen sOTUs were identified in the Enterobacteriaceae family.

Inside were 41, 12, 67 and 16 sOTUs Bacillus, Staphylococcus, Chrysobacterium, And Kokuria type, respectively. Sixteen samples were positive ListeriaOne person tested positive CampylobacterAnd no one Salmonella.

Notably, related SODUs S. Entrica And Shigella/Escherichia found in samples from five countries, whereas C. Jejuni There were Romanian, French and Portuguese models. Most of these pathogens were relatively rare.

Alpha diversity varies significantly between sample types and countries. For example, samples from Portugal had fewer sOTUs than Norway and France, whereas samples from Norway, Hungary and France had similar levels of alpha diversity.

Similar results were observed for the phylogenetic diversity of Faith. Country differences were less pronounced when analyzes were restricted to samples from cleaning vessels, but were significant when only surface samples were considered.

Handles had the highest alpha diversity based on observed features, whereas sponges had the lowest. Principal component analysis (PCA) showed a trend of microbiota clustering by sample type and country. Although the microbiota were similar in cleaning fabrics and sponges, their similarity was greater across countries than between fabrics and sponges.

Surface samples were grouped by country, thus indicating that the microbiota was more similar in surface samples within a country than in a particular surface sample across countries. However, some exceptions to this finding were observed. For example, the microbiota in French handles was more similar to that in Hungarian handles than in other French surface samples.

Some bacteria in sponges and cloths were found in significantly different proportions between countries compared to surface samples. Sink samples had relatively high bacterial counts that varied significantly between countries.

Eight genera/families were identified as major microbiota, including Acinetobacter, Enterobacteriaceae, Pseudomonas, Psychrobacter, Bacillus, Staphylococcus, Anhydrobacter, And Chrysobacterium. this, Pseudomonas, Anhydrobacter, And Acinetobacter All samples contained the same taxa, which also exhibited high mean relative abundance.

Anhydrobacter, Pseudomonas, And Enterobacteriaceae were identified as major sOTUs. The core microbiota varied in relative abundance between sample species and countries. Among major microorganisms, relatively abundant Psychrobacter, Chrysobacterium, Enterobacteriaceae, Pseudomonas, And Anhydrobacter varies considerably between countries.

There were significant differences Acinetobacter And Staphylococcus Between sample types, the highest concentrations were found in moist samples obtained from sinks, cloths and sponges, and handles, respectively. Likewise, Bacillus revealed significant differences between sample types, with the lowest in moist samples.

Conclusion

Despite considerable variation in kitchen standards, eating habits and food preparation practices, the dominant kitchen microbiota was identified as comprising eight taxa at the genus/family level, with three dominant bacteria at the sOTU level.

Overall, the study results expand the knowledge base of kitchen microbes. Future studies should relate these results to food safety behaviors and their impact on human health.