Tracking the Sources of Antibiotic Resistance Genes in an Urban Stream during Wet

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Ernest Townsend
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1 1 2 Tracking the Sources of Antibiotic Resistance Genes in an Urban Stream during Wet Weather using Shotgun Metagenomic Analyses 3 4 Darshan Baral, a,# Bruce I. Dvorak, a David Admiraal, a Shangang Jia, b Chi Zhang, b and Xu Li a,* a Department of Civil Engineering, University of Nebraska, Lincoln, NE, b School of Biological Sciences, University of Nebraska, Lincoln, NE Running Head: Relative Contribution of Sources to Microbes in Stream * Address Correspondence to Xu Li, xuli@unl.edu # Current Address: HDR, Inc., Omaha, NE, Total Number of Pages: 12 Total Number of Tables: 3 Total Number of Figures: 5 S1

2 TABLES Table S1. Water quality parameters for the water samples collected from the base flow and the wet weather flow. Category Year Month Turbidity Surfactants Conductivity TSS (NTU) (mg/l) (µs/cm) (mg/l) JUN SEP SEP Base Flow 2015 JUN SEP JUN AUG SEP JUL AUG JUN Wet 2015 JUL Weather SEP Flow JUL AUG AUG S2

3 Table S2. Relative standard deviation (RSD) of the SourceTracker results based on five independent runs. Sink Wet Weather Water Storm Drain Outfall Water Source SourceTracker Results based on taxa Mean Contribution (%) RSD (%) SourceTracker Results based on ARGs Mean Contribution (%) RSD (%) Base flow Embankment Soil Storm Drain Outfall Water Streambed Sediment Unknown Sanitary Sewage Street Sweepings Unknown S3

4 25 26 Table S3. Significant correlations between microbial taxa and ARGs. Genus ARG Type ARG adec adek multidrug Acinetobacter mdfa mdtk unclassified histidine kinase Actinoplanes Aeromonas beta.lactam class C beta lactamase Amycolatopsis Bradyrhizobium Caldimonas multidrug mexy Cellulomonas Chryseobacterium multidrug adec otra tetracycline tet43 Conexibacter Enhydrobacter multidrug adec adek S4

5 Genus ARG Type ARG Frankia Gordonia tetracycline otra Hydrogenophaga multidrug mexy Janthinobacterium multidrug multidrug transporter Kitasatospora Leptothrix multidrug mexy Lonsdalea multidrug mdta otra tetracycline Marmoricola tet43 Mesorhizobium Methylibium multidrug mexy Methylobacterium Microlunatus tetracycline otra Micromonospora Microvirga tetracycline otra S5

6 Genus ARG Type ARG Mycobacterium tetracycline otra Nitrososphaera Nocardia otra tetracycline Nocardioides tet43 Pantoea multidrug emrb EmrB QacA family major facilitator transporter major facilitator superfamily transporter mdta mexe omp36 ompf TolC otra tetracycline tet43 Patulibacter S6

7 27 Genus ARG Type ARG adec emrb mdta multidrug multidrug transporter Pseudomonas omp36 ompf polymyxin arna unclassified histidine kinase Pseudonocardia tetracycline otra Rhodococcus tetracycline otra Rubrivivax multidrug mexy tetracycline otra Rubrobacter Sorangium Sphaerotilus multidrug mexy Streptacidiphilus Streptomyces S7

8 28 FIGURES Figure S1. Heat map showing the major genera (relative abundance 0.5% in at least one sample) in the 38 environmental samples within 7 sample types. The genus information is listed on the left and the phylum information on the right of the heat map. S8

9 Figure S2. Heat map showing the abundance of the major ARGs (relative abundance 0.5% in at least one sample) in the 38 environmental samples with 7 sample types. The individual ARGs are listed on the left and the corresponding antibiotic types are listed on the right of the heat map. S9

10 Figure S3. The correlation between the abundance of A. orientalis and the total abundance of all resistance genes in all 38 samples. S10

11 Figure S4. PERMANOVA results based on Bray-Curtis distance showing the comparisons between different sample types based on (A) microbial taxa and (B) ARGs. Size and color of the circles both represent the R 2 values. Circles are shown only for significant R 2 at a confidence level of 95% (p<0.05). S11

12 Figure S5. Network analysis showing the strong correlations (Spearman s ρ>0.8, p<0.01) between bacterial genera (open circles), between ARGs (closed circles with colors), and between individual bacterial genera and ARGs. The size of the nodes is proportional to the number of strong correlations associated with the nodes. S12

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