Additional file 2 of Long-read metagenomic sequencing reveals shifts in associations of antibiotic resistance genes with mobile genetic elements from sewage to activated sludge
Creators: name: Dai, Dongjuan
name: Brown, Connor
name: Bürgmann, Helmut
name: Larsson, D. G. Joakim
name: Nambi, Indumathi
name: Zhang, Tong
name: Flach, Carl-Fredrik
name: Pruden, Amy
name: Vikesland, Peter J.
Publisher: name: figshare
Year: 2022
Subjects: subject: Microbiology
subject: FOS: Biological sciences
subject: Genetics
subject: Environmental Sciences not elsewhere classified
subject: Ecology
subject: Biological Sciences not elsewhere classified
subject: Plant Biology

description: Additional file 1: Fig. S1. Size and mass distribution of extracted DNA after purification. Measurement was conducted on an Agilent high sensitivity TapeStation. This analysis demonstrated that 13.4% of extracted DNA has fragment smaller than 4851 bp, likely resulted from mechanical cell lysis of bead-beating in the extraction process. Fig. S2. VirSorter predicted numerous phages in the raw or assembled nanopore reads. (a). Both raw and assembled nanopore reads produced thousands of viral contigs. Cat1: VirSorter category 1 (most confident phage read/contig); Cat2: Virsorter category 2: (intermediate confidence phage read/contig); cat4: VirSorter category 4 (confident prophages). (b) Taxonomy of the best hits for each mobileOG present on the VirSorter-classified reads. (c) The majority of mobileOG-db hits (290 of 312) had identity values less than 60% and bitscore values under 100. (d) Only four shared mobileOGs were detected (mobileOG_000109022: clpB; chaperone, mobileOG_000314698: insF, integrase; mobileOG_000363469: intF, integrase; mobileOG_000712576: Lambda like terminase). Fig. S3. Alignment accuracy (%) of identified ARG sequences in nanopore reads to their reference genes. The alignment accuracy shows the percentage of base pairs in a nanopore read matching the reference ARG. Asterisks indicate significant difference (p&lt;0.01) in alignment accuracies between ARGs located in plasmids and those in chromosomes. Fig. S4. The percentage of total number of unique ARGs being co-located with non-plasmid MGEs (including transposase, integrase, or recombinase genes) on the same nanopore reads mostly decreased (&lt;1% - 21.5%). Examples of hallmark genes that were detected include transposase genes include matches with multiple IS family transposase (e.g., IS3, IS5, IS6, IS91, IS1595) from various species, DDE transposase, etc. Integrase genes include integron integrase, site-specific integrase, and intl1. Recombinase genes include multispecies recombinase protein family, tnpR, etc. “Other” category MGEs refer to matches with mobileOG-db that were not components of integrative, transposable, or conjugative elements. Examples include repA and toxin-antitoxin systems, among others. Fig. S5. Length (kb) distribution of nanopore reads from influent (IN) and activated sludge (AS) samples from five WWTPs located in India (IND), United States (USA), Switzerland (CHE), Sweden (SWE), and Hong Kong (HKG). Fig. S6. Percentage of ARG abundance co-located with hallmarks of transposable, integrative, conjugative and (other) element types. for each ARG class in the ten samples (red Asterix indicate statistically element type-drug class pairs, inferred with the null hypothesis of equal proportions). The percentage was calculated by dividing ARG abundance co-located with non-plasmid MGEs by ARG abundance within a certain ARG class. Box plots shows summary statistics (median, 75 and 25 percentiles, minimum and maximum) in the ten samples. TE: transposable element. Fig. S7. Percentage of ARG abundance from different phyla for plasmid-borne or chromosome-borne ARGs in an influent (IN) or activated sludge (AS) sample. Phylum identification for plasmid-borne or chromosome-borne ARGs was based on output from the PlasFlow pipeline, based on host taxonomy of reference plasmids or whole genome databases. The phylum identification agreed with the outputs from the ARMA pipeline. ARG-carrying nanopore reads with no phylum identified were labeled as unclassified. Fig. S8. Fate of putative pathogens from influent to AS. (a) Percent abundance of ARGs carried in putative pathogens and (b) percent abundance of these putative pathogens in the whole microbial community (independent of whether the pathogen carries an ARG) in influent and activated sludge samples from the five WWTPs. Putative pathogens were limited to those classified as critical top priority pathogens (e.g., Enterobacteriaceae, A. baumannii) by WHO and/or as ESKAPE pathogens. Fig. S9. Network analysis illustrating that ARGs were all associated with pathogen-containing taxonomic groups in influent (a) and activated sludge (b) in samples from the WWTP in the United States (USA). Fig. S10. Network analysis illustrating that ARGs were all associated with pathogen-containing taxonomic groups in influent (a) and activated sludge (b) in samples from the WWTP in Switzerland (CHE). Fig. S11. Network analysis illustrating that ARGs were all associated with pathogen-containing taxonomic groups in influent (a) and activated sludge (b) in samples from the WWTP Sweden (SWE). Fig. S12. Network analysis illustrating that ARGs were all associated with pathogen-containing taxonomic groups in influent (a) and activated sludge (b) in samples from the WWTP in Hong Kong (HKG). Fig. S13. Individual ARGs that significantly increased (a) or decreased (b) in their abundances (gc/Gb) from influent to AS. Numbers denoted in panel b indicate the median percent reduction in gene abundance from influent to AS. Fig. S14. Fate of mobile ARGs across the WWTPs sampled here. Log-fold change in ARG abundance was calculated as the log of the ratio between AS abundance and influent abundance (normalized as gene copies per Gbp). Fig. S15. ARG detection rate and profile change with sequencing depth varying from 0.68 to 3.3 million reads. Bar chart by indicates ARG class profile with sequencing depth. MDS plot considers individual ARG abundances. Both influent (IN) and activated sludge (AS) samples from India (IND), Hong Kong (HKG), and Switzerland (CHE) were subsampled to the lowest depth (0.68 million reads), 1.0, half of all reads (1.35, 1.6) and full depth (2.7, and 3.3 million reads). Table S1. Sampled WWTPs from five locations. Table S2. Nanopore read statistics. Table S3. Converted ARG abundances from prior studies* of wastewater treatment plants. Table S4. Comparative sequencing depth, counts and base pairs in ARG-carrying reads/contigs identified in this study to exemplar references applying Illumina or ONT sequencing platforms to study wastewater samples from WWTPs. Table S5. Percentage of ARG abundance on plasmids for each ARG class and sample location.