High-throughput microbial culturomics using automation and machine learning - Nature Biotechnology

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High-throughput microbial culturomics using automation and machine learning - Nature Biotechnology
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High-throughput microbial culturomics using automation and machine learning

). All colonies on plates were then isolated on CAMII on day 6 and subjected to taxonomy identification by 16S rRNA sequencing. To quantify differential initial growth of genera, the number of detectable colonies of each genus on each day was normalized to their total number of colonies on day 6 to calculate the proportion of detectable colonies at each day.gDNA of picked isolates were extracted in 384-well format using a silica bead beating-based protocol adapted from a prior study.

The resulting amplicon libraries were manually pooled and subjected to gel electrophoresis on E-Gel EX Agarose Gels, 2% . Expected DNA bands were excised from gel and extracted by Wizard SV Gel and PCR Cleanup System following the manufacturer’s instructions to remove PCR primers and adapter dimers.

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