CAM-L is an interactive resource of cultured bacteria isolated from colorectal adenomas, adenocarcinomas, metastases and adjacent normal tissues. It provides curated metadata, genome and quality metrics, functional annotations with virulence factors. CAM-L is a valuable resource for elucidating causal microbiome contributions to colorectal cancer development.
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Patients
Isolation Sites
Phyla
Isolates
Species
Novel species
We collected tissue specimens from two clinical cohorts (FAP and SPORADIC) From these patients, we collected material from adenomas, primary tumors, liver metastasis as well as paired adjacent (and presumed healthy) colon, and liver tissues.
We only show the traditional species names that do not take into account distinct genomic clusters within the species.
Hover and click on the data points for more insights.
After biopsy, tissue samples were snap-frozen to minimize the exposure time to oxygen until bacterial culturing. We iteratively optimized culturing conditions to maximize the number of species that could be cultivated from each sample. The success rate of bacterial cultivation was much higher for colon tissues compared to liver.
Click on an agar to see which species can be cultivated from it.
Our isolated bacterial strains generally show high completeness (median = 99.67 %) and low contamination (median = 0.39 %), indicating an overall high quality of genome assemblies with very few exceptions.
We annotated the bacterial genomes using Bakta.
Click on an isolate to see its gene annotations.
We annotated the bacterial genomes using eggnog-mapper.
Click on an isolate to inspect detected pathways and their genes.
We predicted virulence factors by DIAMOND-alignment of our bacterial genome sequences against the VFDB (Virulence Factor Database), which catalogs known virulence factors from various pathogens.
Filter by virulence factor identities.
Virulence factors and associated genes share the same color.
Click on an isolate to explore its virulence factors.
This tool allows you to explore the data on your own by creating custom plots.
Simply drag and drop the variables into the different aesthetics (e.g. x, y, color, size).
This infers the most suitable plot type, but you can also change it manually.
Use the controls at the bottom to adjust font size, add titles, change color, ...
CAVE: Not all combinations of variables result in reasonable plots.
Finally, you can download the plot in any format you like.