Exercise Microbiome continued

This post is a presentation of supplemental data of a Chinese study of pre-diabetic men whose microbiome was assessed after being put on an exercise protocol. The hypothesis was that elements of the microbiome separated those who responded to the treatment from those you did not. The previous post also examined a exercise/microbiome study in children.

The microbiome of Men in Mice

Supplemental table 2 of the Liu study gives us a snap shot of the species found in over 25% of the men that changed in response to 12 weeks of exercise. Up arrows and down arrows have been drawn to draw attention to those species that changed.

The Alistripes genus has been associated with inflammation, mental health and cancer. [2] This post will not go into the referenced publication. The Alistripes putredinis increase in the non-responders was not significant.

This table might require coming back to. No change was seen in these species in the non-responders. There were significant changes in the select species of bacteria in the responders, even if the fold change hovered around 1. Does exercise cause bacteriophage or something to become more lytic?

But the mice aren’t exercising

Figure S7. This figure relates back to Figure 5 in the official text reviewed on this site. The authors used Whole-genome shotgun metagenomic sequencing was performed for fecal samples from mice receiving FMT and the original fecal slurries. (A) Responders (B) Non-responders The reference point is time.

Note that the relative abundance changed a lot in the responder human samples (blue) did not parallel the same time dependent change in mice (cyan). On the other hand, the microbiome from the non-responders changed, for the most part, similarly over time whether in an exercising human or a sedentary mouse.

Of short chain fatty acids, branched chain amino acids, and aromatic amino acids

Short chain fatty acids have been discussed plenty on this site. The supplemental data [1] have been rearranged to shown results from mice and men in the say grouping. The direction of the change are pretty consistent even if the relative numbers of bacteria are not. It is interesting to note that butyrate and propionate increase in the responders regardless of whether or not the bacteria are in an exercsing human or a sedentary mouse.

Then we get into the branched chain amino acid data as BCAA are associated with type 2 diabetes, insulin resistance. that is hypothesized to involve the mammalian target of rapamycin complex 1 (mTORC1), which is activated by BCAA. [3]

Aromatic amino acids were of interest as tryptophan is a precursor of serotonin/5-HT.

Turning responders into non-responders

1. Gavage containing saline and  glycerol
2. Gavage FMT from responders
3. Gavage FMT + branched chain amino acids in the drinking water at (1.5 mg/kg.bw per day, weight ratio, isoleucine: leucine: valine= 0.8:1.5:1) during the 4-week FMT period.

No difference was seen in the body weight, % fat, or % lean in these groups of mice (not shown in this post). 

*p < 0.05, **p < 0.01 between R-FMT + water and R-FMT + BCAAs; #p < 0.05, ##p < 0.01, and ###p < 0.001 when compared with PBS-FMT + water.

Prevotella copri was attributed to be a source of branched chain amino acids in the feces of non responders as well as a source of insulin resistance according to previous studies cited by the authors. The authors argued that other species that utilize short chain amino acids as an energy source may also explain the decrease in BCAA in the circulation of the responders. Data were expressed as mean ± SEM (n = 6 mice/group). Significance was calculated by ANOVA followed by Turkey’s multiple comparison tests. Dots with different colors represent individual mice receiving FMT from different human donors.

And non-responders into responders

Liu and coauthors went in the opposite and tested the hypothesis that supplementation with short chain fatty acids (in the drinking water) would make the FMT from the non-responders “work” in reversing the obese phenotype in terms of glucose and insulin functioning.  The mice not in group C were given pH adjusted water.

1. Gavage containing saline and glycerol
2. Gavage FMT from non-responders
3. Gavage FMT + drinking water with 50mM butyrate and 25.9 mM propionate.

No difference was seen in the body weight, % fat, or % lean in these groups of mice (not shown in this post).  One interesting aspect of this section is that the branched chain AA producing non-spending FMT was not worse than the PBS FMT.  s\

*p < 0.05, **p < 0.01 and ***p < 0.001 between NR-FMT + water and NR-FMT + SCFAs; #p < 0.05, ##p < 0.01, and ###p < 0.001 when compared with PBS-FMT + water. Data were expressed as mean ± SEM (n = 6 mice/group). Significance was calculated by ANOVA followed by Turkey’s multiple comparison tests. Dots with different colors represent individual mice receiving FMT from different human donors

These authors attributed the positive effects of butyrate and propionate supplementation to secretion of GLP-1 and peptide YY.   Absent from these results are the affect of SCFA and BCAA alone, without FMT, and in combination.  Do SCFA and BCAA act in opposite directions and cancel each other out? 

References

1. Liu Y, Wang Y, Ni Y, Cheung CKY, Lam KSL, Wang Y, Xia Z, Ye D, Guo J, Tse MA, Panagiotou G, Xu A. Gut Microbiome Fermentation Determines the Efficacy of Exercise for Diabetes Prevention. Cell Metab. 2020 Jan 7;31(1):77-91.e5. free article
2. Parker BJ, Wearsch PA, Veloo ACM, Rodriguez-Palacios A. The Genus Alistipes: Gut Bacteria With Emerging Implications to Inflammation, Cancer, and Mental Health. Front Immunol. 2020 Jun 9;11:906. PMC free article
3. Bloomgarden Z. Diabetes and branched-chain amino acids: What is the link? J Diabetes. 2018 May;10(5):350-352.
4. rnoriaga-Rodríguez M, Mayneris-Perxachs J, Contreras-Rodríguez O, Burokas A, Ortega-Sanchez JA, Blasco G, Coll C, Biarnés C, Castells-Nobau A, Puig J, Garre-Olmo J, Ramos R, Pedraza S, Brugada R, Vilanova JC, Serena J, Barretina J, Gich J, Pérez-Brocal V, Moya A, Fernández-Real X, Ramio-Torrentà L, Pamplona R, Sol J, Jové M, Ricart W, Portero-Otin M, Maldonado R, Fernández-Real JM. Obesity-associated deficits in inhibitory control are phenocopied to mice through gut microbiota changes in one-carbon and aromatic amino acids metabolic pathways. Gut. 2021 Dec;70(12):2283-2296 PMC free article