Search bioRxiv⌕ Search

bioRxiv · 10.64898/2026.02.26.708305

Microbial community dynamics in a traditional Swiss mountain cheese over 142 years of cheesemaking

Abstract

The history of cheesemaking is deeply intertwined with the evolution of microbial communities, from spontaneous fermentation to modern, standardized practices. Despite centuries of refinement, the most profound shifts in cheese production occurred in the last century, driven by advances in microbiology and production technologies. These changes have shaped the bacterial and viral communities within cheese, yet the specific impacts remain underexplored. Using shotgun metagenomics and 16S rRNA gene amplicon sequencing approaches, we examined microbial community changes in Raclette du Valais, a traditional Swiss cheese, using preserved cheese wheels from 1875 to 2017 from the same alpine dairy in Switzerland. Our results reveal that significant shifts in microbial community composition coincide with changes in production practices. Notably, the oldest cheese harbored a distinct bacterial community, dominated by Lactiplantibacillus paraplantarum, Streptococcus thermophilus, Pseudolactococcus laudensis, and taxa commonly associated with the gut environment, indicative of spontaneous fermentation and the use of calf stomach for milk coagulation. Functionally, we can also track the rise and fall of antibiotic resistance genes mirroring their use. Furthermore, we found that domestication of lactic acid bacteria predates the studied period, and that bacteriophage genera detected in 1875 are representatives of those commonly found in modern cheesemaking. These findings highlight how microbial communities have adapted to changing production methods and how human intervention, through practices like antibiotic use in animal husbandry, has influenced these ecosystems in remote alpine cheesemaking. Significance StatementCheesemaking relies on complex microbial ecosystems shaped by long-standing human practices, yet how these communities responded to the modernization of food production has remained largely unknown. By analyzing DNA preserved in historical cheese wheels from a single alpine dairy, we examine microbial community changes across a key technological transition. We show that modernization impacted bacterial composition and functional potential, that cheese microbiomes record the rise of agricultural antibiotic use, and that major cheese-associated phages and domesticated starter bacteria were already established over a century ago. These findings demonstrate that historical cheeses preserve long-term microbial records and offer a glimpse how changes in food production practices shape fermented-food microbiomes.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Somerville, V., Meola, M., Nunes-Richards, A., Bengtsson-Palme, J., Neukamm, J., Majander, K., Pla-Diaz, M., Turgay, M., Moineau, S., Haueter, M., Berthoud, H., von Ah, U., Luedin, P., Schuenemann, V. J., Shani, N.. 2026-02-27. Microbial community dynamics in a traditional Swiss mountain cheese over 142 years of cheesemaking. https://doi.org/10.64898/2026.02.26.708305

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

A population-scale landscape of the subgingival microbiome reveals divergent routes to periodontal dysbiosis

Periodontitis is an archetypical mucosal inflammatory disease in which microbiome dysbiosis at the tooth-epithelial interface interacts with host genetic and behavioral risk factors to drive immune-mediated tissue destruction. Although subgingival microbiome compositional shifts are thought to parallel disease severity, microbiome variation at the population-level and its relationship to periodontal clinical phenotypes and disease-modifying factors remain poorly defined. Here, we use unsupervised manifold learning to map the compositional landscape of the subgingival microbiome in 1,355 adults spanning periodontal health to severe periodontitis. We identified eight latent microbiome states organized along a branching continuum from eubiosis to dysbiosis. An intermediate microbial configuration marked ecological destabilization and bifurcation into two distinct periodontitis-associated dysbiotic trajectories, distinguished by links to gingival inflammation and smoking. Although the microbiome trajectories broadly tracked periodontal destruction, a minority of individuals showed discordant microbiome-clinical phenotypes, with some individuals with periodontitis retaining otherwise eubiotic microbiomes enriched for low-abundance pathobionts, while some cases of health or mild disease had highly dysbiotic communities, suggesting distinct host susceptibility. Together, these findings define a population-scale ecological landscape of the subgingival microbiome, reveal divergent trajectories to periodontal dysbiosis, and highlight heterogeneity in the relationship between microbial community structure and clinical disease expression.

microbiology↗

Rapid and largely reversible shifts in the canine fecal metabolome during dietary change

Diet can rapidly change the fecal metabolome, but less is known about recovery after the original diet is restored. We used untargeted UPLC-MS metabolomics to analyze 72 fecal samples from nine Pumi dogs during an owner-managed switch from dry food to raw food and back to dry food. Diet phase accounted for a large proportion of variation in both ionization modes. More than 13,000 LC-MS features changed at the first sampling point after the switch to raw food, with a similarly large response after return to dry food. Among features significant in both comparisons, more than 99% changed in opposite directions. At the final sampling point, no positive-mode (ESI+) features and only 13 negative-mode (ESI-) features differed from the second dry-food baseline under the same threshold. BARF-associated patterns persisted in analyses excluding individual dogs and in pedigree-adjusted candidate models, although individual feature effects depended on normalization. Putative metabolites from several biochemical classes differed in their response and recovery. The fecal metabolome therefore changed rapidly and returned largely toward baseline, with differences among dogs.

microbiology↗

Taxonomic and functional concordance between full-length ONT 16S and ONT shotgun metagenomics in the canine gut microbiome

Background: Full-length Oxford Nanopore Technologies (ONT) 16S rRNA sequencing provides a scalable view of microbial community composition and can support phylogeny-based functional prediction, but it is not equivalent to shotgun metagenomics. We asked which biological conclusions are preserved when the same canine fecal specimens are profiled by full-length ONT 16S and ONT whole-genome shotgun (WGS) sequencing, and how their agreement depends on analytical scale, reference representation and classifier. Methods: Ninety-seven fecal specimens from 51 dogs were profiled with both assays from the same DNA extract. Functional profiles predicted from NanoASV/NanoPredict with PICRUSt2 were compared with WGS-supported KEGG Ortholog (KO) profiles generated by Kadath. Taxonomy was benchmarked in a source-genome-matched RefSeq universe and in a host-specific DogMAG universe using minitax and Kraken2. Agreement was evaluated at whole-profile, feature-abundance, detection, between-sample structure and biological-inference scales. Age-associated transfer was assessed with dog-aware continuous mixed models, grouped signed-score analyses and paired/dog-blocked PERMANOVA. Results: Functional whole-profile concordance was high: median within-sample CLR Spearman correlations ranged from 0.781 to 0.860 across developmental strata, while between-sample functional structure remained significant by Mantel (rho=0.543) and Procrustes (r=0.693; both p=0.001). Feature-wise transfer was substantially weaker (median KO-wise CLR Spearman=0.318). Continuous age-associated KO slopes showed substantial cross-assay concordance (Spearman=0.727; signed-score Spearman=0.753; direction agreement=77.9%), although 1,290/5,258 eligible KOs retained significant assay-by-age interactions. Taxonomically, exact genus/species abundance agreement was much lower than agreement in between-sample ecological structure. Host-specific DogMAG improved species-level median Spearman from 0.261 to 0.656 for minitax SpeciesEstimate and from 0.181 to 0.512 for Kraken2. The classifier effect was independent of reference choice: under both RefSeq and DogMAG, minitax yielded stronger 16S-WGS concordance than Kraken2, with all eight prespecified RefSeq paired genus/species endpoints and all 10 DogMAG primary paired endpoints significant after BH correction. The same ordering extended to developmental inference, with DogMAG genus/species age-slope concordance of 0.795/0.799 for SpeciesEstimate versus 0.693/0.702 for Kraken2. Taxonomic Aitchison PERMANOVA detected age-associated structure in every assay/reference/classifier/rank combination, whereas age-by-assay interactions were consistently significant but small (R2 approximately 1.1 to 2.2%). Stricter NanoASV identity thresholds removed substantial 16S abundance without improving species-level agreement. Conclusions: The extent of cross-assay agreement depends on the level of analysis. Full-length ONT 16S preserves broad functional organization, ecological structure and much of the direction of age-associated change, but exact fine-rank composition, individual-feature abundance and effect magnitude remain assay dependent. Host-specific reference representation substantially narrows the taxonomic gap, and classifier choice exerts an additional independent effect: within the same matched reference set, minitax consistently yields stronger 16S-WGS concordance than Kraken2 across abundance, detection, ecological-distance and developmental-inference endpoints. Full-length ONT 16S is therefore well suited to broad ecological screening and hypothesis generation, whereas WGS remains preferable when conclusions depend on quantitative fine-rank composition, directly supported gene content or precise feature-level effect estimates.

microbiology↗