five

Microbial community responses to diverse DOM

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NIAID Data Ecosystem2026-05-10 收录
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https://www.ncbi.nlm.nih.gov/sra/ERP187087
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Microorganisms form the base of aquatic food webs and play a key role in the global carbon cycle by decomposing dissolved organic matter (DOM). Climate change is predicted to shift the composition of DOM in northern freshwaters, with unknown consequence for the resident bacterial communities and wider ecosystem processes. Here, we grew an artificial, six-species bacterial community on seven diverse DOM sources that varied in their bioavailability and were representative of predicted future compositional changes in northern waters. Using full-length 16S metabarcoding (Oxford Nanopore Technologies), we characterized how the relative abundances of the six species varied with DOM source and over time. DNA from the communities was extracted using a CTAB phenol-chloroform method. We then amplified the entire 16S rRNA gene in each sample using the Oxford Nanopore Technologies rapid barcoding kit SQK-RAB204 (Oxford Nanopore Technologies, UK) and followed the manufacturer's protocol to prepare amplicons with the 27F-1492R primer pair. PCR products were pooled into libraries following the SQK-16S024 Flongle protocol (Oxford Nanopore Technologies, UK) and sequenced for 24 hours. A ZymoBIOMICS? Microbial Community Standard II Log Distribution (Zymo Research, USA) control sample was extracted and sequenced alongside the samples. Raw sequencing reads were base called using Guppy version 6.0.6 (Oxford Nanopore Technologies, UK) and we discarded any reads beneath an initial quality cut-off of Q = 7. We used Guppy Barcoder (provided within Guppy) to remove barcode and adapter sequences from each read and removed reads that were shorter than 1.3kb and longer than 1.6kb using Nanofilt v.2.8.0. We have deposited the base called, demultiplexed and processed reads, with one fastq file per sample (i.e. DOM source, time point and replicate). Sample metadata, including sample IDs and full sample information, in addition to analysis scripts used to process these metabarcoding data are found in the Figshare repository at the following link: https://figshare.com/s/e281b3501e23ddc4f739.
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2026-01-17
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