Reacción a "The relationship between gut bacteria and diseases could be overestimated"

Various changes (dysbiosis) in the normal microbiota have been linked to a wide range of diseases, such as diarrhea, constipation, Crohn's disease, ulcerative colitis, Alzheimer's, autism, cancer, and more. However, despite intense research in this field over the past few decades, "normal microbiota" and "dysbiosis" remain vague and imprecise terms, influenced by the significant interindividual microbial diversity found in healthy individuals. Furthermore, it is not entirely clear whether dysbiosis is the cause or the consequence of these diseases.

The authors have developed a machine learning program to predict fecal microbial load (the absolute abundance of microorganisms in feces) from relative abundance data, which is provided by metataxonomic (microbial amplicon sequencing) and metagenomic (total microbial DNA sequencing) analyses. Using these algorithms, they analyzed a large number of previous studies, relating the composition of the gut microbiota to total microbial load. Similarly, various diseases are linked to a lower (diseases associated with diarrhea) or higher (conditions associated with constipation) total microbial load than expected. The model does not establish causal relationships between total microbial load and diseases, but the authors believe that this total microbial load could be a significant confounding factor when associating diseases with gut microbes. Accounting for this total microbial load could allow researchers to focus specifically on a few key species for each disease. In other words, it does not have immediate practical utility but could be highly important for future studies addressing these microbe-disease associations.

Limitations:

- Although the model seems robust for estimating total microbial load from relative abundance data, the authors believe it can be refined in future studies.

- The relationship between total microbial load and certain microbial species is not very clear. That is, it is unknown whether changes in total microbial load drive changes in species composition or vice versa. This is crucial since some species (e.g., Clostridioides difficile, Escherichia coli producing colibactin, etc.) are clearly linked to diseases.

- The model has only been applied to prokaryotic populations (bacteria and archaea) in the gut. The study did not address microbial load in other biotypes, such as viruses or eukaryotic organisms (fungi, yeasts, parasites), which could also be relevant.