Task 3.1 - Geographical and temporal variability of the respiratory metagenome (m1-12): Stored samples from the PreDicta cohort, acquired in 5 European countries during 2 years, will be used. UMAN will produce the metagenomic metadata, as described in methodology. Dissimilarity of metagenomes among locations and seasons will be analysed using beta diversity matrices, principal component analysis (PCA) and hierarchical clustering. Input will be provided to T5.1 for health-disease modelling and T3.2.

Task 3.2 - Longitudinal patterns (m13-30): Samples from the CURE cohort will be processed, sequenced (Milestone 2) and analysed to describe longitudinal patterns of the microbial ecology, with linear mixed models. Trajectories of the microbial ecology will be characterised using principal coordinates analysis (PCoA) of Bray-Curtis dissimilarity matrices, weighted UniFrac distances and MrGBP. Metadata will be provided towards T5.2 (time-series model) and T1.3 (dysbiosis phenotypes).

Task 3.3 - Microbial co-occurrence networks (m25-48): Data from T3.1 and T3.2 (Milestone 5) will be used to infer microbial interactions using phylogenetic networks based on the ecological indices (diversity, richness, and abundance), correlation networks based on r coefficients and evolutionary relationships based on the identification of prophage sequences within the genome of bacteria and CRISPR-Cas spacer sequences. The results will be used to optimise the T5.3 model. UMEÅ, SIAF & BRFAA will contribute to the analyses