scholarly journals A High Protein Calorie Restriction Diet Alters the Gut Microbiome in Obesity

Nutrients ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 3221
Author(s):  
Tien S. Dong ◽  
Kayti Luu ◽  
Venu Lagishetty ◽  
Farzaneh Sedighian ◽  
Shih-Lung Woo ◽  
...  

Background: High protein calorie restriction diets have shown clinical efficacy for obesity, but the mechanisms are not fully known. The intestinal microbiome is a mediator of obesity and preclinical data support an effect of high protein diet (HPD) on the gut microbiome of obesity, but there are few studies in humans. Methods: To address this, we conducted a dietary intervention trial of 80 overweight and obese subjects who were randomized to a calorie-restricted high protein diet (HPD) (30% calorie intake) or calorie-restricted normal protein diet (NPD) (15%) for 8 weeks. Baseline dietary intake patterns were assessed by the Diet History Questionnaire III. Longitudinal fecal sampling was performed at baseline, week 1, week 2, week 4, week 6, and week 8, for a total of 365 samples. Intestinal microbiome composition was assessed by 16S rRNA gene sequencing. Results: At baseline, microbial composition was associated with fiber and protein intake. Subjects on the HPD showed a significant increase in microbial diversity as measured by the Shannon index compared to those on the NPD. The HPD was also associated with significant differences in microbial composition after treatment compared to the NPD. Both diets induced taxonomic shifts compared to baseline, including enrichment of Akkermansia spp. and Bifidobacterium spp. and depletion of Prevotella spp. Conclusion: These findings provide evidence that weight loss diets alter the gut microbiome in obesity and suggest differential effects of HPDs compared to NPDs which may influence the clinical response to HPD.

Circulation ◽  
2013 ◽  
Vol 127 (suppl_12) ◽  
Author(s):  
Marielle F Engberink ◽  
Wieke Altorf-van der Kuil ◽  
Elizabeth J Brink ◽  
Stephan J Bakker ◽  
Marleen A van Baak ◽  
...  

Background: Mild metabolic acidosis may result in elevated blood pressure (BP). Several formulas to estimate dietary acid load have been developed. However, studies in which these formulas have been validated are limited. Objectives: To validate and/or improve existing formulas for dietary acid load and to examine the association between dietary protein, acid load and BP. Methods: We performed a randomized 14d crossover dietary intervention involving 37 healthy subjects (age: 21±2 y) who consumed individualized, isocaloric diets that were either low or high in protein (0.5 versus 2.0 g protein/kg BW/d). Duplicate portions of the provided diets were collected and analysed for energy and nutrients. We used two measures to characterize dietary acid load (i.e. PRAL and NEAP). Urinary Net Acid Excretion (NAE; i.e. titratable acid + ammonium - bicarbonate) was analysed. BP was measured according to standardized procedures. Results: Mean dietary intakes significantly differed between the low and high protein diet, resulting in significantly different acid load values (Table 1, all p<0.001). The correlation between PRAL and NAE was 0.08 in the low protein diet and 0.62 in the high protein diet. For NEAP the correlations were 0.27 and 0.32. PRAL explained 69% of the variance of NAE, which could not be improved by adding other variables to the formula. Systolic BP was 108.4±7.5 and 109.5±8.0 mmHg on the low and high protein diet respectively (p=0.25). Conclusion: PRAL predicts NAE reasonably well in healthy adults for normal to high protein intake. PRAL can be influenced by diet, but this cannot be clearly attributed to protein intake alone. PRAL does not seem to influence short-term BP in healthy adults with normal BP.


2016 ◽  
Vol 150 (4) ◽  
pp. S117
Author(s):  
Jonathan Jacobs ◽  
Lixin Wang ◽  
Mulugeta Million ◽  
Joseph R. Pisegna ◽  
Yvette Tache

2021 ◽  
Vol 12 ◽  
Author(s):  
XiaoLing Zhang ◽  
TianWei Xu ◽  
XunGang Wang ◽  
YuanYue Geng ◽  
Na Zhao ◽  
...  

To improve performance and optimize rumen function in yaks (Bos grunniens), further knowledge on the appropriate dietary protein levels for ruminal microbiota and the metabolite profiles of yaks in feedlot feeding is necessary. Current understanding of dietary protein requirements, ruminal microbiota, and metabolites is limited. In this study, yaks were fed a low-protein diet (L; 9.64%), middle low-protein diet (ML; 11.25%), middle high-protein diet (MH; 12.48%), or a high-protein diet (H; 13.87%), and the effects of those diets on changes and interactions in ruminal microbiota and metabolites were investigated. Twenty-four female yaks were selected, and the effects on ruminal microbiota and metabolites were investigated using 16s rRNA gene sequencing and gas chromatography time-of-flight/mass spectrometry (GC-TOF/MS). Diets containing different protein levels changed the composition of the rumen bacterial community, the H group significantly reduced the diversity of ruminal microbiota (p &lt; 0.05), and the number of shared amplicon sequence variants (ASVs) between the H group and the other three groups was lower, suggesting that the ruminal microbiota community fluctuated more with a high-protein diet. In rumen, Bacteroidetes, Firmicutes, and Proteobacteria were the most abundant bacteria at the phylum level, and Bacteroidetes was significantly less abundant in the MH group than in the L and ML groups (p &lt; 0.05). Prevotella_1, Rikenellaceae_RC9_gut_group, and Christensenellaceae_R-7_group had the highest abundance at the genus level. Prevotellaceae was enriched in the low-protein groups, whereas Bacteroidales_BS11_gut_group was enriched in the high-protein groups. Rumen metabolite concentrations and metabolic patterns were altered by dietary protein levels: organic acid metabolites, antioxidant-related metabolites, and some plant-derived metabolites showed variation between the groups. Enrichment analysis revealed that significant changes were concentrated in six pathways, including the citrate cycle (TCA cycle), glyoxylate and dicarboxylate metabolism, and butanoate metabolism. Network analysis showed promotion or restraint relationships between different rumen microbiota and metabolites. Overall, the rumen function was higher in the MH group. This study provides a reference for appropriate dietary protein levels and improves understanding of rumen microbes and metabolites.


2008 ◽  
Vol 67 (OCE5) ◽  
Author(s):  
F. Vitari ◽  
A. Morise ◽  
M. Formal ◽  
C. Garcia ◽  
K. Mace ◽  
...  

Antibiotics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 180
Author(s):  
Kouki Shimizu ◽  
Issei Seiki ◽  
Yoshiyuki Goto ◽  
Takeshi Murata

The intestinal pH can greatly influence the stability and absorption of oral drugs. Therefore, knowledge of intestinal pH is necessary to understand the conditions for drug delivery. This has previously been measured in humans and rats. However, information on intestinal pH in mice is insufficient despite these animals being used often in preclinical testing. In this study, 72 female ICR mice housed in SPF (specific pathogen-free) conditions were separated into nine groups to determine the intestinal pH under conditions that might cause pH fluctuations, including high-protein diet, ageing, proton pump inhibitor (PPI) treatment, several antibiotic treatment regimens and germ-free mice. pH was measured in samples collected from the ileum, cecum and colon, and compared to control animals. An electrode, 3 mm in diameter, enabled accurate pH measurements with a small amount of gastrointestinal content. Consequently, the pH values in the cecum and colon were increased by high-protein diet, and the pH in the ileum was decreased by PPI. Drastic alkalization was induced by antibiotics, especially in the cecum and colon. The alkalized pH values in germ-free mice suggested that the reduction in the intestinal bacteria caused by antibiotics led to alkalization. Alkalization of the intestinal pH caused by antibiotic treatment was verified in mice. We need further investigations in clinical settings to check whether the same phenomena occur in patients.


2016 ◽  
Vol 146 (3) ◽  
pp. 474-483 ◽  
Author(s):  
Chunlong Mu ◽  
Yuxiang Yang ◽  
Zhen Luo ◽  
Leluo Guan ◽  
Weiyun Zhu

1991 ◽  
Vol 62 (7) ◽  
pp. 628-635
Author(s):  
Masayuki FUNABA ◽  
Hajime NABETA ◽  
Hideo YANO ◽  
Ryoji KAWASHIMA

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