Additional file 2 of Global abundance patterns, diversity, and ecology of Patescibacteria in wastewater treatment plants
Creators: name: Hu, Huifeng
name: Kristensen, Jannie Munk
name: Herbold, Craig William
name: Pjevac, Petra
name: Kitzinger, Katharina
name: Hausmann, Bela
name: Dueholm, Morten Kam Dahl
name: Nielsen, Per Halkjaer
name: Wagner, Michael
Publisher: name: figshare
Year: 2024
Subjects: subject: Microbiology
subject: FOS: Biological sciences

description: Additional file 2: Table S1. Primer sequences used for the in silico coverage analyses. Table S2. Coverages of commonly used 16S rRNA gene primers (V1-V3, V3-V4, V4, V4-V5, and modified V4) for different phyla evaluated by the SILVA r138.1 database with zero and one mismatch. Table S3. Coverages of commonly used 16S rRNA gene primers (V1-V3, V3-V4, V4, V4-V5, and modified V4) for different classes of Patescibacteria evaluated by the SILVA r138.1 database with zero and one mismatch. Table S4. Coverages of commonly used 16S rRNA gene primers (V1-V3, V3-V4, V4, V4-V5, and modified V4) for different phyla evaluated by the MiDAS database 4.8.1 with zero and one mismatch. Table S5. Coverages of commonly used 16S rRNA gene primers (V1-V3, V3-V4, V4, V4-V5, and modified V4) for different classes of Patescibacteria evaluated by the MiDAS database 4.8.1 with zero and one mismatch. Table S6. Primer sequences for the modified V4 primer pair compared with the original V4 primer pair. Table S7. Metadata for wastewater treatment plants. Table S8. Genus level richness comparisons between the data sets obtained by the original and the modified primer pairs. The slope of the observed ASV and Shannon index were predicted by the linear regression analysis using the modified and original primer sets. Table S9. Blast mapping of patescibacterial ASVs to Danish WWTP metagenomic datasets. Three 100% identity mapping with &gt;330 base pair coverage were highlighted in yellow. Table S10. Global distribution of the patescibacterial genera identified as core community members from each country (average relative abundance). Table S11. Core patescibacterial genera identified if all four main process types of activated sludge samples were analysed together and MAG representation of core genera. Table S12. Core patescibacterial genera identified in activated sludge samples from plants with carbon removal (C). Table S13. Core patescibacterial genera identified in activated sludge samples from plants with carbon removal with nitrification (C, N). Table S14. Core patescibacterial genera identified in activated sludge samples from plants with carbon removal, nitrification and denitrification (C,N,DN). Table S15. Core patescibacterial genera identified in activated sludge samples from plants with carbon removal, nitrogen, and enhanced biological phosphorus removal (C, N, DN, P / EBPR). Table S16. List of patescibacterial genera that were characterized as CRAT genera. Table S17. Correlated genus pairs (X and Y) with p value &lt;0.001 and an absolute correlation value &gt;0.5 identified by SparCC network analysis. Table S18. Correlated genus pairs (X and Y) with p value &lt;0.001 and an absolute correlation value &gt;0.5 identified by CoNet network analysis. Table S19. Correlated genus pairs (X and Y) with an absolute weight edge &gt;0.2 identified by SPIEC-EASI network analysis. Table S20. Correlated ASV pairs (X and Y) with p value &lt;0.001 and an absolute correlation value &gt;0.5  identified by SparCC network analysis. Table S21. Correlated ASV pairs (X and Y) with p value &lt;0.001 and an absolute correlation value &gt;0.5 identified by CoNet network analysis. Table S22. Correlated ASV pairs (X and Y) with an absolute weight edge &gt;0.2 identified by SPIEC-EASI network analysis.