MICOM tradeoff value

Hi, I'm trying to build a mouse microbiome model using micom.

During the process, I got a result from micom.workflows.tradeoff.tradeoff and the result show that as tradeoff value increases, the fraction of taxa growing increases also.
According to the community tutorial, tradeoff value is the rate between high community-level biomass production vs. allowing more taxa to grow. Right?
So, in my opinion, there should be a small number of dominant species with high growth rates in order to get high community-level biomass production and the number of overall growing taxa would be declined.
But my result shows very different aspect. (completely opposite)

I wonder if this result is possible. Because If I did something wrong, I have to do again from the start :joy:
I have attached one of the results. And if you need more information, please let me know.

I'll be waiting for the reply. Thanks!

tradeoff.csv (104.3 KB)

1 Like

So sorry, just saw this now. Feel free to ping me on everything MICOM here (@cdiener). During the optimization MICOM tries to distribute growth across taxa as evenly as possible. If all your taxa can grow at very high tradeoff values that is awesome since it means that maximum biomass is perfectly compatible with the observed richness. The decline with lower tradeoff values has something to do with the cutoff for growth we use. We generally don't consider growth rates <1e-6 to be actual growth. So with low tradeoff values, the growth rates overall get smaller and some of those very small growth rates suddenly fall under the threshold. Maybe they were 1e-5 at a tradeoff of 1 and are now 5e-7 for instance. I wouldn't fret about this too much, since you observe 100% of taxa growing at a tradeoff of 1 and that is much better than not running cooperative tradeoff ("none"). So I would stick with a tradeoff of 1.

Thank you for your reply and I understand what are you mean.

But when I tested with the tutorial sample that you provided here(q2-micom | A Qiime plugin for MICOM.) using CarveMe model, not AGORA, the result of micom.workflows.tradeoff.tradeoff had similar tendency of mine.
So I feel confused about the reliability of using CarveMe.

I know CarveMe is just automatically designed and that is not complete, if I do the next analysis like detect community export metabolites or interactions of members, results are a little ambigous.
The reason I'm saying this is because after run the code to search net export fluxes of my sample, there's nothing special differences between normal samples and IBD samples although the genus taxa between those are very different ratio. But the metabolomics analysis data detected some noticeable differences.

So, If my result (nothing special different export change) is right, the differences of values of metabolomic analysis is the result of the change in the health status of the host and if not, there are trouble in using something factors.

I just wonder what your opinion of this.