Is SMETANA able to use a comprehensive medium which simulates the human gut?

[White-Shinobi]

To follow this question metaGEM/issues/111, I also have some questions about the Medium for Carveme and SMETANA.

When I used Carveme to build the GEMs, I used M8+MEU (MEU, the diet metabolites Average EU diet) to gap-fill. When I used SMETANA to get the cross-feeding results, I tried to use the M8 or M8+MEU. However, M8+MEU gave me fewer cross-feeding pairs than M8. May I ask why is the more comprehensive medium gave me fewer results?

The reason to use M8+MEU is because that I want to mimic the human gut environment. But in Carveme paper, I saw a sentence saying " To quantify this cross-feeding plasticity, we applied SMETANA, a mixed-integer linear programming method, to identify metabolic exchanges es- sential for the survival of the community in a minimal medium." So I am wondering, is SMETANA able to use a comprehensive medium to calculate the cross-feeding relationship?

Best, Yue

[franciscozorrilla]

Hi Yue,

So I am wondering, is SMETANA able to use a comprehensive medium to calculate the cross-feeding relationship?

Yes, it should be possible, please read below for my explanations.

When I used Carveme to build the GEMs, I used M8+MEU (MEU, the diet metabolites Average EU diet) to gap-fill. When I used SMETANA to get the cross-feeding results, I tried to use the M8 or M8+MEU. However, M8+MEU gave me fewer cross-feeding pairs than M8. May I ask why is the more comprehensive medium gave me fewer results?

This makes sense, and it has to do with the fact that when you gapfill on a given media, you are telling CarveMe that a given model needs to grow under a given media condition, so it will add metabolic reactions that support growth on that minimal media. Therefore, the richer (i.e. more comprehensive) the gapfilling media then the less reactions that will be needed to be added to the model in order to support growth, while a minimal media would require more reactions to be added to the model since there are less metabolic building blocks (i.e. nutrients) to work with.

Similarly, when it comes to simulation media, you should indeed expect to get fewer cross-feeding interactions in the richer (i.e. more comprehensive) compared to the less-rich media. The reason for this is that the interactions represent exchanges where the microbes are unable to obtain a particular necessary nutrient metabolite from the media, and must therefore exchgange it with another member (presumably with a different set of metabolic capacities) in order to grow. For example, if you have a complete media i.e. models can uptake any metabolite that they want, then you would get 0 exchanges between communuity members, because the species would just grow directly from the media. On the other hand, if you have a very minimal media, then this would encourage the community members to interact in order to compensate for each others' auxotrophies.

In fact, if you gapfill models on M8+MEU and then simulate those models in M8+MEU media then I would expect that no interactions are predicted. Again, this has to do with the fact that the models should be growing directly on the media that they were gapfilled for. In your case, I would probably try gapfilling on M8+MEU and then simulating on M8 or MEU.

Best, Francisco

[White-Shinobi]

Hi Francisco,

Thank you for your quick response.

In your case, I would probably try gapfilling on M8 and then simulating on M8+MEU.

My research question is how gut microbiome cross-feed each other in human colon. So the gut microbiome is exposed to the gut environment all the time. The environment is not changing, so why do we need to gapfill and then simulate on different mediums?

Best, Yue

[franciscozorrilla]

Hi Yue,

I think some flux balance analysis & genome scale metabolic modelling literature may be helpful for to understand the underlying theory.

So the gut microbiome is exposed to the gut environment all the time. The environment is not changing

Actually, in real life the gut environment/media composition does change over time, for example in response to changes in diet or e.g. if you are fasting.

so why do we need to gapfill and then simulate on different mediums?

The answer to this is explained the comments above. In summary, the gapfilling is used to ensure that the models can grow in a given media composition. You can check this by running an FBA simulation using one of your gapfilled models with the gapfilling media (e.g. M8 + MEU), the model should be able to grow. Next try an FBA simulation using the non-gapfilled version of that model, likely it will not be growing. Now try simulating the community of gapfilled models using SMETANA with the same gapfilling media, you should not get any exchanges predicted because the community members can independently grow directly from the media as a consequence of gapfilling. Now, if you start removing metabolites from the media that you used for gapfilling, then the species will start to interact with each other in order to compensate for the missing metabolites in the media.

In your case, I would probably try gapfilling on M8 and then simulating on M8+MEU.

I apologize, here I meant to say that you should gapfill on M8+MEU and then simulate on M8 or MEU. Again, the reasoning here is that you make the models functional (i.e. gapfilling) on a given media, and then simulate on a subset of that media to see how the community may compensate for the missing metabolites through metabolic interactions.

Best wishes, Francisco