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Page 4 of 15 Kamilari et al. Microbiome Res Rep 2025;4:3 https://dx.doi.org/10.20517/mrr.2024.47

Table 1. Information about the collected samples
Sample ID Country Area Traditional/industrial Smoked Wine Preservatives
C1 Cyprus Lemesos Industrial Yes Yes Yes
C2 Cyprus Lemesos Industrial Yes Yes Yes
C3 Cyprus Pitsilia Traditional Yes Yes No
C4 Cyprus Pitsilia Traditional Yes Yes No
C5 Cyprus Pitsilia Traditional Yes Yes No
C6 Cyprus Pitsilia Traditional Yes Yes No
C7 Cyprus Nicosia Industrial Yes Yes No
C8 Cyprus Nicosia Industrial Yes Yes No
C9 Cyprus Nicosia Industrial Yes Yes No
C10 Cyprus Nicosia Industrial Yes Yes No
C11 Cyprus Nicosia Industrial Yes Yes No
C12 Cyprus Nicosia Industrial Yes Yes No
C13 Cyprus Nicosia Industrial Yes Yes No
C14 Cyprus Nicosia Industrial Yes Yes No
C15 Cyprus Pitsilia Traditional Yes Yes No
C16 Cyprus Pitsilia Traditional Yes Yes No
C17 Cyprus Pitsilia Traditional Yes Yes No
C18 Cyprus Nicosia Industrial Yes Yes Yes
C19 Cyprus Nicosia Industrial No Yes Yes
C20 Cyprus Nicosia Industrial No Yes Yes
C21 Cyprus Nicosia Industrial No Yes Yes
C22 Cyprus Nicosia Industrial No Yes Yes
G1 Greece Mytilini Industrial Yes No Yes
G2 Greece Mytilini Industrial Yes No Yes
G3 Greece Mytilini Industrial Yes No Yes
G4 Greece Mytilini Traditional Yes No Yes
G5 Greece Mytilini Traditional Yes No Yes
G6 Greece Mytilini Traditional Yes No Yes
G7 Greece Mytilini Traditional Yes No Yes
G8 Greece Mytilini Traditional Yes No Yes

Illumina MiSeq barcoded sequencing for 16S rRNA gene in bacteria and ITS region in fungi
For the 16S rRNA region and ITS loci amplification, the library preparation and sequencing were executed
in an Illumina MiSeq platform as previously described [24-26] .

Data interpretation
Raw fastq sequences filtering, and alpha and beta diversity analyses were executed using Qiime 2 version
2021.11, as previously described . Samples were rarefied in 17784 for bacteria and 16957 for fungi.
[27]
Statistically significant differences among sausages from different areas or manufacturing conditions based
on their beta diversity were assessed using non-parametric permutational analysis of variance
[28]
(PERMANOVA) , as described by Kamilari et al. . Taxonomy assignment for 16S rRNA gene sequences
[25]
and ITS regions into OTUs was based on the q2-feature-classifier against the Greengenes 13_8 99% OTUs
[29]
[30]
reference sequences and the UNITE ITS database (9_12 release) , respectively. Sequence filtering was
[31]
conducted to filter out incomplete taxonomies that could not be detected at the order level. The
identification of microbial signatures was performed using the LEfSe algorithm [25,32] and the random forest
algorithm in Qiime2, as described previously [33-35] . Statistically significant correlations between area/
processing conditions and identified microbiota were estimated using CoNet , and visualized using
[36]