Freshwater monitoring by nanopore sequencing (Guppy v3.1.5 base calls). Freshwater monitoring by nanopore sequencing (Guppy v3.1.5 base calls)

1. Summary We conducted metagenomic analyses of freshwater samples (400 ml) from nine distinct locations (samples 1-9, with 9.1 and 9.2 as biological replicates from the same site) along a ~12 kilometre trajectory of the River Cam in Cambridge, East Anglia, UK. This was done at three time points in 2018: on April 15th, June 17th, and August 19th. 2. Workflow and Data Samples were filtered through 0.22 µM pore-sized nitrocellulose membranes. We then performed DNA extractions with a modified DNeasy PowerWater protocol (Qiagen, Hilden, Germany). 400 ml of deionised water were subjected to the same workflow as negative controls (N). DNA isolates were barcoded according to their location or negative control ID, amplified for full-length 16S rDNA (~1.5 kb) and complemented by a positive control (P) containing a defined microbial community standard which features eight distinct bacterial species (ZymoBIOMICS D6305, Zymo Research, Irvine, CA, USA). The resulting amplicons were sequenced with one MinION flow cell per time point (LSK109 kit with R9.4 pore chemistry, Oxford Nanopore Technologies). The MinION instrument was run for approximately 48 hours, until no further sequencing reads were obtained. Raw fast5 files were recorded and locally base called using Guppy (v3.1.5); please note that we also provide base calls from the outdate Albacore software (v2.3.1) here (https://www.ebi.ac.uk/ena/data/view/PRJEB32906). Reads were demultiplexed and adapters trimmed using porechop (v0.2.4). The only non-default parameter was ‘--check_reads’ (set to 50,000 to increase the subset of reads to search for adapter sets). Next, we removed all reads shorter than 1.4 kb and longer than 1.6 kb using filtlong (v0.2.0). Here, we deposit the de-multiplexed and processed reads as one fastq file per time point and location (or control). 3. Analyses and Media We encourage you to read about our findings with this data via bioRxiv (https://www.biorxiv.org/content/10.1101/2020.02.06.936302v2). Please also visit the project website (www.puntseq.co.uk) and Twitter account (https://twitter.com/puntseq) for more details and updates.