Additional file 1 of Microbial community regulation and performance enhancement in gas biofilters by interrupting bacterial communication
Creators: name: Wang, Yong-Chao
name: Lin, Yu-Ting
name: Wang, Can
name: Tong, Zhen
name: Hu, Xu-Rui
name: Lv, Ya-Hui
name: Jiang, Guan-Yu
name: Han, Meng-Fei
name: Deng, Ji-Guang
name: Hsi, Hsing-Cheng
name: Lee, Chung-Hak
Publisher: name: figshare
Year: 2022
Subjects: subject: Space Science
subject: Microbiology
subject: FOS: Biological sciences
subject: Ecology
subject: Biological Sciences not elsewhere classified

description: Additional file 1: Figure S1. The schematic diagram of biofilters setup. Figure S2. Schematic diagram of biofilm adhesion strength test. Figure S3. Effect of different dosage of Rhodococcus sp.BH4 on biofilm formation. Figure S4. (a) AHL quenching rate and (b) quorum quenching activity towards the exogenous AHL in the biofilm samples on Days 25, 45, 65 and 90. Figure S5. The sample distance matrix obtained based on the bray Curtis algorithm. The results were used to test whether the difference between groups is significantly greater than the difference within the group. Figure S6. Chao1 index, number of OTUs, Shannon index and pielou_e index in BF and QQBF biofilms. Figure S7. Relative abundance of biomarkers at the phylum level in (a) BF and (b) QQBF. The biomarkers were chosen through Kruskal-Wallis test. Figure S8. Comparison of relative abundance of QS-related bacteria in BF and QQBF biofilms at day 25 and 90. Figure S9. Comparison of gene expression levels in microbial samples at day 90 between BF and QQBF based on metagenomic analysis. Figure S10. Comparison of the number of up-regulated and down-regulated genes in microbial samples (BF vs QQBF) at day 90 of BF and QQBF based on metagenomic analysis. Figure S11. Differential gene enrichment results in microbial samples at day 90 of BF and QQBF based on KEGG database annotations. Figure S12. Up-regulation of QS genes in BF biofilm samples compared to QQBF in QS regulatory pathways based on metagenomic analysis. Note: The fold difference in relative abundance of genes in BF and QQBF were treated using Exponential. Figure S13. Test results of the degradation of toluene by Rhodococcus sp. BH4. Table S1. Development of waste gas biofilter technology. Table S2. Composition of the nutrient solution. Table S3. The operating conditions of the two biofilters. Table S4. The results of Ergun equation fitting at the 25th day and the 65th day. Table S5. Statistic differences in EPS concentrations. Table S6. Quenching rate (k) of AHLs in sludge samples at different times. Table S7. The description and relative abundance of QS-related genes in BF and QQBF samples. Table S8. Topological properties of the empirical pMENs of the biofilm communities in BF and QQBF biofilms during the operation and their associated random pMENs. Table S9. Keystone species' centrality indexes of networks in biofilm communities sourced from BF and QQBF biofilms. Table S10. Taxonomic information and average abundance of keystone taxa observed in ecological networks in biofilm communities sourced from BF and QQBF biofilms. Table S11. Typical QS genes description and function in QS regulatory pathways in BF and QQBF biofilm samples based on metagenomic analysis. Table S12. Summary of the role of Rhodococcus sp. BH4 in bioreactors. Supplementary Method S1. The biofilm adhesion strength test. Supplementary Method S2. 16S rDNA sequencing. Supplementary Method S3. Metagenomics Sequencing Analysis. Supplementary Method S4. The calculation of biofilter performance and pressure drop curve fitting methods.