Maintenance of a high degree of biodiversity in homogeneous environments is poorly understood. A complex cheese starter culture with a long history of use was characterized as a model system to study simple microbial communities. Eight distinct genetic lineages were identified, encompassing two species: Lactococcus lactis and Leuconostoc mesenteroides. The genetic lineages were found to be collections of strains with variable plasmid content and phage sensitivities. Kill-the-winner hypothesis explaining the suppression of the fittest strains by density-dependent phage predation was operational at the strain level. This prevents the eradication of entire genetic lineages from the community during propagation regimes (back-slopping), stabilizing the genetic heterogeneity in the starter culture against environmental uncertainty.

Background: Next generation sequencing (NGS) technologies can be applied in complex microbial ecosystems for metatranscriptome analysis by employing direct cDNA sequencing, which is known as RNA sequencing (RNA-seq). RNA-seq generates large datasets of great complexity, the comprehensive interpretation of which requires a reliable bioinformatic pipeline. In this study, we focus on the development of such a metatranscriptome pipeline, which we validate using Illumina RNA-seq datasets derived from the small intestine microbiota of two individuals with an ileostomy. Results: The metatranscriptome pipeline developed here enabled effective removal of rRNA derived sequences, followed by confident assignment of the predicted function and taxonomic origin of the mRNA reads. Phylogenetic analysis of the small intestine metatranscriptome datasets revealed a strong similarity with the community composition profiles obtained from 16S rDNA and rRNA pyrosequencing, indicating considerable congruency between community composition (rDNA), and the taxonomic distribution of overall (rRNA) and specific (mRNA) activity among its microbial members. Reproducibility of the metatranscriptome sequencing approach was established by independent duplicate experiments. In addition, comparison of metatranscriptome analysis employing single- or paired-end sequencing methods indicated that the latter approach does not provide improved functional or phylogenetic insights. Metatranscriptome functional-mapping allowed the analysis of global, and genus specific activity of the microbiota, and illustrated the potential of these approaches to unravel syntrophic interactions in microbial ecosystems. Conclusions: A reliable pipeline for metatransciptome data analysis was developed and evaluated using RNA-seq datasets obtained for the human small intestine microbiota. The set-up of the pipeline is very generic and can be applied for (bacterial) metatranscriptome analysis in any chosen niche.

Summary: Increasing interest in new beer types has stimulated the search for approaches to extend the metabolic variation of brewers’ yeast. Therefore, we tested two approaches using non‐conventional yeast to create a beer with lower ethanol content and a complex aroma bouquet. First, the mono‐culture performance was monitored of 49 wild yeast isolates of Saccharomyces cerevisiae (16 strains), Cyberlindnera fabianii (9 strains) and Pichia kudriavzevii (24 strains). Interestingly, both C. fabianii and P. kudriavzevii isolates produced relatively more esters compared with S. cerevisiae isolates, despite their limited fermentation capacity. Next, one representative strain of each species (Sc131, Cf65 and Pk129) was applied as co‐culture with brewers’ yeast (ratio 1:1). Co‐cultures with Cf65 and Pk129 resulted in a beer with lower alcohol content (3.5, 3.8 compared with 4.2% v/v) and relatively more esters. At higher inoculum ratios of Cf65 over brewers’ yeast, growth inhibition of brewers’ yeast was observed, most likely caused by competition for oxygen between brewers’ yeast and Cf65 resulting in a reduced level of ethanol and altered aroma profiles. With this study, we demonstrate the feasibility of using non‐conventional yeast species in co‐cultivation with traditional brewers’ yeast to tailor aroma profiles as well as the final ethanol content of beer.