Spatial and functional differentiation of microbial biofilms in a traditional cheese ripening environment

Abstract

Biofilms in historic buildings represent stable microbial ecosystems shaped by long-term environmental filtering. We investigated bacterial and fungal communities forming biofilms on walls and ceilings in a 19th-century cheese ripening cellar in Poland, characterized by low temperature, high humidity, and minimal light - conditions resembling natural subterranean habitats. Using high-throughput 16 S rRNA and ITS sequencing, we revealed distinct taxonomic and predicted functional profiles associated with surface type (wall vs. ceiling) and material (brick vs. stone). The wall biofilms exhibited greater taxonomic and functional diversity, with enrichment in heterotrophic, fermentative, and polymer-degrading taxa and pathways, whereas ceiling biofilms showed predicted enrichment in aerobic, stress-tolerant, and potentially methanogenic lineages. The co-occurrence network analysis revealed more complex and tightly connected associations in wall biofilms, dominated by Actinobacteriota (21-97%) and Ascomycota (60-97%), suggesting stable ecological organization despite the limited sample size. Environmental factors, such as pH, redox potential, and electrolytical conductivity, explained a substantial proportion of the variance in the microbial diversity and predicted functional traits. Overall, this study highlights traditional ripening cellars as semi-natural built ecosystems that sustain specialized, spatially structured microbiomes. The results provide new insights into microbial adaptation, functional potential, and ecological resilience in heritage food environments.

Keywords: Bacterial microbiome; Biofilms; Built environment microbiome; Metagenomics; Mycobiome; Ripening rooms.

Fig. 1

Alpha (a and b) and beta (c and d) diversity. The boxplots corresponds to the bacterial (a) and fungal (b) biodiversity indices: Simpson, Shannon, and Pielou index and represents the diversity between the samples. The Principal Coordinates Analysis (PCoA) illustrates the variability of bacteria (c) and fungi (d) between the biofilms.

Fig. 2

Relative abundance (%) of top 10 bacterial (a) and fungal (b) phyla. representing the microbial community identified in the biofilm samples.

Fig. 3

Relative abundance of top 10 bacterial (a) and fungal (b) genera (%), representing the microbial community identified in the biofilm samples. Differences in the relative abundance of dominant taxa at the genus level as a function of the sampling location (walls vs. ceiling) (c and d) and the wall construction material (brick vs. stone) (e and f).

Fig. 4

Redundancy analysis (RDA) biplot depicting the relationship between the bacterial (a) and fungal (b) communities and the main physicochemical parameters of the biofilm samples.

Fig. 5

Heat map showing the predicted functional activity of microorganisms assigned to different functional groups in the analysis of 16 S rRNA amplicon sequences. The color intensity represents the level of a given function in each sample: dark red - higher predicted functional activity, blue - lower activity, white - neutral activity (close to zero).

Fig. 6

Heat map showing the predicted functional activity of microorganisms assigned to different functional groups in the analysis of ITS region sequences. The color intensity represents the level of a given function in each sample: dark red - higher predicted functional activity, blue - lower activity, white - neutral activity (close to zero).

Fig. 7

Network interactions of the 20 most common ASVs of the biofilm microbiota, where nodes are marked with colors corresponding to the cluster level. Only strong and statistically significant correlations (|r| > 0.6, p < 0.05) were included in the network.