Coinfections in COVID-19

COSMIC: Co-infections and Secondary Microbial Infections in COVID-19

COSMIC is a collaboration between researchers and clinicians at the Quadram Institute, University of Edinburgh, University of Bristol and University of Birmingham that aims to use metagenomics of respiratory samples to identify the bacteria, fungi, and viral co-infections present in patients with COVID-19.

Data will be shared publicly when it is generated, watch this space for updates!

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Have got permission for the other authors to share our previous bid to give an idea of what we were planning for this.

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Certainly happy to get updates on your efforts. If we are successful with our funding we are willing to include any prevalent bacterial spp in our pipeline.

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If you want someone to look at the virome (both informatically and with culturing), let me know!

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Looks great - what sequencing platforms are you using? And what’s the metagenomic pipeline?

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Nanopore for sequencing, and the pipeline will be the Loman usual approach (I say this because I do not know the jns and outs of that bit, I’m the bit between clinic and analysis)!

We’re definitely hoping to detect the virome @Ben and have included RNA/cDNA for that reason. Sensitivity of that will be interesting to find out!

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@m.j.cox and @Ben, I also like offer my help with the virome. At the Quadram, we’re establishing a viral mock community based on bacteriophages (so safe to handle and easy to produce) for our virome studies (RNA+DNA).

I haven’t tried it yet on the Loman nanopore approach, so that will be interesting.

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Hi Vicky - for DNA metagenomics we do the “3 peaks” method for DNA isolation to preserve fragment length, and then we like a de novo assembly based approach where possible (https://github.com/SamStudio8/reticulatus) or mapping for the low abundance stuff. For RNA metagenomics we use a cDNA strand-switching method we call “SMART metagenomics” after DNase treatment and then on the bioinformatics something like KrakenUniq against a large database to rapidly filter down to plausible matches, then switch to a reference mapping approach to finer scale analysis.

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Sounds great @Evelien, mock communities are a pain to make and so useful methodologically

I agree with Mike, happy to test it if you need external lab validation, Evelien

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Very cool. We are doing something similar - excl. viruses though and on a smaller scale, but will be very interesting to compare data once they start accumulating.

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Hi Nick - any details on the SMART metagenomics?
Just talking about that for new grant, and I remind your post