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    • We used total calorimetry to assess

    2018-10-23

    We used total calorimetry to assess the RMR of the subject, which includes simultaneous measurement of total RMR via direct calorimetry, and aerobic RMR via respirometry (Kaiyala and Ramsay, 2011). Simultaneous assessments of RMR in various species via direct calorimetry and respirometry by our group and others have uncovered large discrepancies (Walsberg and Hoffman, 2005, 2006; Burnett and Grobe, 2013, 2014), which we interpret as an index of non-aerobic processes. For example, we recently described a large contribution (7 to 12%) of non-aerobic RMR in both C57BL/6J and FVB/NCrl strains of mice (Burnett and Grobe, 2013, 2014). It is worth noting that contributions of non-aerobic RMR are variable even within a species. We also determined that one week of a 45% high fat diet in C57BL/6J mice specifically suppresses non-aerobic RMR (Burnett and Grobe, 2014). Because non-aerobic resting metabolism exists in humans (Pittet et al., 1974, 1976), we are only beginning to appreciate its physiological significance (Burnett and Grobe, 2014). We also demonstrated that risperidone treatment led to an overall reduction in observed taxa (OTUs) found within the gut microbiome (Fig. S6) as well as selectively suppressing growth of organisms under p-Cresyl sulfate conditions, similar to the environment found within the mammalian intestinal tract. The observed suppression of non-aerobic RMR was found to be 16% of the total RMR for the animal. The magnitude of this difference is substantial. For example, for a 2000kcal/day human, roughly 80% of total energy expenditure (1600kcal/day) occurs in the form of RMR. A 16% reduction in total RMR would therefore equate to increasing energy retention by ~260kcal/day, nearly equivalent to consuming an extra standard McDonald\'s cheeseburger (290kcal) (McDonald\'s Nutrition, 2015) each day — a decidedly obesigenic maneuver. Chronic treatment with risperidone led to specific alterations in the microbiota. We found a significant enrichment in Allobaculum and Turicibacter spp., both members of the Firmicute family Erysipelotrichaceae, which has been associated with diet-induced obesity in mice (Ravussin et al., 2011). Interestingly, members of this family have been shown in several independent studies to change in abundance in response to dietary fat intake (Cani et al., 2008; Fleissner et al., 2010; Turnbaugh et al., 2008). Aneroplasma spp., a member of the Mollicutes class, was also found to be more abundant following risperidone treatment. Previously, Gordon et al. performed metagenomic sequencing and transcriptomics on diet-induced obesity cecal samples of the microbiome, revealing that Mollicutes are enriched for pathways involved in the import and fermentation of simple sugars and host glycans (Turnbaugh et al., 2008) thereby providing a mechanism for increased energy harvest from an obesigenic microbiota. We also found a depletion of Alistipes spp. and Akkermansia spp. in risperidone treated animals compared to controls, both of which have been associated with a lean microbiota (Ridaura et al., 2013). Therefore, our findings offer evidence that risperidone treatment alters the composition of the microbiome which suppresses resting metabolic rate and leads to weight gain. Because suppression of energy expenditure was conferred by the transfer of either the whole microbiota or the phage fraction from risperidone treated mice, we propose that non-aerobic RMR is regulated in part by the gut microbiota. Therefore, manipulation of resting metabolic rate, specifically via the gut microbiome, represents a largely untapped approach to treating obesity. Preventing alteration of the microbiome or the effects of the altered microbiome on RMR, may prove beneficial for patients undergoing risperidone treatment. The following are the supplementary data related to this article.
    Conflict of interest
    Funding This work was supported by grants from the NIH (HL098276 and HL084207 to JLG, and R01AI108255 to JK), the American Heart Association (15SFRN23730000 to JLG), the American Diabetes Association (1-14-BS-079 to JLG), the National Science Foundation (MCB-1244021 to JK), and the University of Iowa Fraternal Order of Eagles\' Diabetes Research Center (to JK & JLG). Additional support was provided by the University of Iowa Department of Microbiology. BJW was supported by an undergraduate research fellowship from the American Physiological Society. CMLB was supported by the University of Iowa Medical Student Research Program. ANC was supported by the University of Iowa Dean\'s Graduate Research Fellowship and an Alfred P. Sloan Foundation Scholarship. OD was supported by an Alfred P. Sloan Foundation Scholarship.