typemat12.bsky.social
Microbial (meta)genomics researcher @sangerinstitute
interested in genomic epidemiology and evolutionary dynamics of STIs/NTDs/AMR in complex samples. Views my own.
https://www.sanger.ac.uk/person/beale-mathew/
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507 following
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Agreed - my first thought when I saw this was "why not just use ENA anyway?". I'm open to being convinced there is a reason to prefer SRA (even with this).
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It's Bezos's space rocket (which in no way looks like anything else)
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And @carmcdhume.bsky.social recently did a blog about our field work using this method in Zimbawe sangerinstitute.blog/2025/02/17/s...
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Although here we have used T. pallidum as a model, we think this approach has broad applications for larger pathogen genomes (bacterial, fungal, parasite), and we hope others can make use of these approaches for different pathogens.
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We also built a @nextflow.io pipeline for rapid data processing, and a prototype shiny app for interactive data interpretation.
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And we then deployed the method to a low-resource laboratory with our collaborators @thruzim.bsky.social BRTI in Zimbabwe as part of an ongoing genital ulcer study. The final assay can be performed in <2 days and costs <£13/sample.
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We designed a 59-amplicon multiplex primer scheme which performs with high sensitivity (<qPCR Ct 32), with sequencing performed on MinION Flongle cells (24 samples per run), and high concordance between ONT amplicon SNP calls and Illumina WGS.
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With novel (previously undescribed diversity), it functions more like a highly sensitive MLST - randomly occurring SNPs will occur by chance in amplicons, but we have many more amplicons than a typical MLST scheme so we have more opportunity to detect novelty.
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This enables high resolution reconstruction of a WGS phylogeny using a small % of the genome (3.6% of T. pallidum genome here). The method recovers known sublineages (<20 SNPs apart) with high precision
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We can use this to identify information rich regions, and then hierarchically select the optimal combination of regions to ensure coverage of all sublineages. We demonstrate this using a 59-amplicon scheme for Treponema pallidum (causative agent of syphilis)
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When we identify SNPs discriminating individual finescale sublineages (e.g. <20 SNPs apart), the SNPs are scattered along a bacterial genome. However, if we consider discriminatory SNPs for many sublineages together, by chance we find positional clustering
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Genomic pathogen surveillance is costly & challenging but multiplex amplicons eg @joshquick.bsky.social primalscheme works for viruses. Applying to larger (bacterial) genomes means compromise. For known pop structures, we identify key ancestral SNPs, then find regions which maximise discrimination
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Think it's a week