# data[].attributes.headline
INTRODUCTION                                                                                                                                                                                                                              

# data[].attributes.subject
INTRODUCTION                                                                                                                                                                                                                              

# data[].attributes.headline
METHODOLOGY                                                                                                                                                                                                                              

# data[].attributes.subject
METHODOLOGY                                                                                                                                                                                                                              

# data[].attributes.headline
DISCUSSION & FUTURE OUTLOOK                                                                                                                                                                                                                             

# data[].attributes.subject
DISCUSSION & FUTURE OUTLOOK                                                                                                                                                                                                                             

# data[].attributes.body
In comparing the two diets, we found that the Microbiome Enhancer Diet resulted in:

# data[].attributes.body
1. Reduces metabolizable, available energy to the host, as more energy is instead channelled to to the gut microbiome. Evidenced by:

Increased microbial fermentation

Increased fecal and serum SCFA levels

Increased fecal energy loss

# data[].attributes.body
2. Change in species abundance

Particularly more fibre degraders + SCFA producers

# data[].attributes.body
3. Supports weight loss by maintaining a calorie/energy deficit.

116 kcal/day deficit

# data[].attributes.body
A current idea in weight management that small changes are more effective for weight loss than making a major lifestyle shift. Small changes are more sustainable and easier to keep up with for the patient.

That is, a lesser calorie deficit maintained consistently over a longer period of time is more effective than a severe deficit over a shorter period of time.

# data[].attributes.attachment_caption
Fig 1. (a) Energy lost through feces by participants on the WD vs. MBD (gCOD/day). (b) Host metabolizable energy based on the proportion of COD to dietary intake. (c) Calculated host non-metabolizable energy (kcals). 

# data[].attributes.headline
                                                1                                              The microbiome enhancer diet (MBD) reduced host metabolizable energy 

# data[].attributes.subject
                                                1                                              The microbiome enhancer diet (MBD) reduced host metabolizable energy 

# data[].attributes.body
Addressing the primary endpoint: What are the differences of host metabolizable energy between the different diets (Western diet vs. microbiome enhancer diet)?

The authors used chemical oxygen demand (COD), which converts energy intake in kcals to grams COD, to measure host-metabolizable energy

Findings:

The microbiome enhancer diet (MBD) showed higher levels of fecal energy loss compared to western diet (WD)

MBD resulted in lower percentage of metabolizable energy available for the host compared to WD

Higher levels of calculated host non-metabolizable energy in MBD compared to WD

# data[].attributes.attachment_caption
Fig 2a. Fecal bacterial 16s rRNA gene copy number (surrogate of biomass) on MBD vs. WD

# data[].attributes.headline
                                                2                                              MBD demonstrates a significant effect on 16s rRNA gene copy number 

# data[].attributes.subject
                                                2                                              MBD demonstrates a significant effect on 16s rRNA gene copy number 

# data[].attributes.body
Addressing the secondary endpoint: Investigating the changes in microbiota composition due to diet

Findings:

Significant increase in 16s rRNA gene copy number, a surrogate of fecal bacterial biomass

Figure 1a showed that the MBD produced a significant decrease in host metabolizable energy, with more energy being channeled to with the energy being channeled to the feces shown through the increase in fecal energy loss (Fig 1a). Thus, the increase in 16s rRNA gene copy number (Fig 2a) which is a surrogate of biomass, can contribute to the higher mean daily fecal weight seen with the MBD (Fig 4a). Additionally, a proportion of the additional weight is attributed to the increase in 16s rRNA gene copy number (biomass).

# data[].attributes.body
To accomplish this study, the authors needed to compare two different diets. To do this, they specially formulated a 'Microbiome Enhancer Diet' (MBD), and a 'Western Diet' (WD).

# data[].attributes.body
In order to conduct a study, you have to have participants! Here is the inclusion criteria the authors used:

Age range: 18-45 years old

Based in the USA

BMI: ≤ 30 kg/m^2

Weight stable

No underlying medical conditions ('otherwise healthy')

No antibiotic use within 3 months

# data[].attributes.body
Randomized crossover design:

Design in which every participant is exposed to the same two treatments, but in different orders.

Example:

Group 1: Treatment A , then Treatment B

Group 2: Treatment B, then Treatment A

# data[].attributes.body
There were a lot of different methods used, but here are some of the most unique ones, or the most important ones!

# data[].attributes.body
1. Corbin, D.E., et al. 2023. Host-diet-gut microbiome interactions influence human energy balance: a randomized clinical trial. Nature Communications. 14(1): 3161. doi: 10.1038/s41467-023-38778-x

2. Hill O.J., et al. 2013. The Importance of Energy Balance. Endocrinology. 9(2): 111-115. Doi: 10.17925/EE.2013.09.02.111

3. Roberts S.B., 2022. Dietary Energy. Advances in Nutrition. 13(6): 2681-2685. doi:10.1093/advances/nmac092

4. Blundell J.E., 2015. Appetite control and energy balance: impact of exercise. Obesity Reviews. 1: 67-76. Doi: 10.1111/obr.12257

5. Brown H.E., 2016. Family-based interventions to increase physical activity in children: a systematic review, meta-analysis and realist synthesis. Obesity Reviews. 17(4): 345-360. doi:10.1111/obr.12362

6. Ryan. D. 2020. Energy Balance and Weight Loss for Diabetes Remission. Diabetes Spectrum. 33(2):117-124. Doi: 10.2337/ds20-0005

7. Montenegro. J., et al. 2023. Exploring the Influence of Gut Microbiome on Energy Metabolism in Humans. Advances in Nutrition. 14(4): 840-857. Doi: 10.1016/j.advnut.2023.03.015

8. Wang. Y., et al. 2020. Nuciferine modulates the gut microbiota and prevents obesity in high-fat diet-fed rats. Experimental Molecular Medicine. 13(1): 1-24. Doi: 10.1038/s12276-020-00534-2

9. Zhang. X., et al. 2020. Dietary cholesterol drives fatty liver-associated liver cancer by modulating gut microbiota and metabolites. Gut. 70(4): 761-774. Doi: 10.1136/gutjnl-2019-319664

# data[].attributes.headline
                                                3                                              Microbial composition associated with host energy balance on MBD vs. WD 

# data[].attributes.subject
                                                3                                              Microbial composition associated with host energy balance on MBD vs. WD 

# data[].attributes.body
Addressing the secondary endpoint: What are the changes in microbiota composition due to diet?

Species alpha and beta diversity metrics were calculated using R.

Finding:

Beta diversity of the gut microbiome was significantly different, and a stark separation between the two diets was discovered

This indicates that the increase in bacterial biomass seen with MBD when compared to WD was accompanied by a change in microbial diversity.

# data[].attributes.body
Introduction: Jia Zhen Lu

Methods: Kingsley

Results: Cherry

Discussion & Outlook: Izzy

Editing, consolidation, and aesthetics: all

# data[].attributes.attachment_caption
Fig 3. (a) Fecal short chain fatty acids. (b) Serum short chain fatty acids. 

# data[].attributes.headline
                                                4                                              Microbiome enhancer diet (MBD) increased microbial fermentation 

# data[].attributes.subject
                                                4                                              Microbiome enhancer diet (MBD) increased microbial fermentation 

# data[].attributes.body
To further explore the diet-induces changes in microbial composition and the use of the additional energy being channeled to feces, the authors looked into microbial fermentation.

Finding:

MBD increased microbial fermentation, denoted by higher amount of acetate, proprionate, and butyrate in feces and serum, contributing to a higher amount of total SCFAs

# data[].attributes.body
Maximized availability of dietary substrates to the gut microbiome

Four components:

Dietary fibre

Resistant startch

Large food particle size

Limited processed food

Ex. whole grains, lentils, fruits, vegetables

# data[].attributes.body
Served as a negative control

Formulated to be representative of typical diet based on a person living in the United States

Opposite of the four components in MBD, but still in easily digestible form

Ex. Processed & cured meats, butter, cheese

# data[].attributes.body
Metabolic ward provides a controlled environment

Allows for causative results to be determined

Ensures that the sole difference between the groups is due to the assigned diet

Randomized crossover design

All participants are put in both conditions

Each person acts as their own control, eliminating inter-subject variability. This is very important as the gut microbiome varies a lot from person to person.

# data[].attributes.attachment_caption
Supplementary Fig 4b. Alpha diversity measures of richness and evenness of the microbiomes on WD vs. MBD

# data[].attributes.body
Alpha diversity was shown to be statistically insignificant between the microbiomes on WD and MBD

This tells us that the species richness and evenness of each group is not significantly different.

# data[].attributes.body
Not much specifics on pathways of the human host-diet-gut microbiome interactions

Cannot confidently establish if individual effects are due to diet, microbiome, or both

Not easily generalizable to general populations

Selection bias due to small sample size

Controlled laboratory environment

No subgroup analysis

Does not account for affects of culture on diet

Control is the Western Diet, indicating a bias towards the Global West

# data[].attributes.body
How would the comparative effects of the Microbiome Enhancer Diet change if compared against a diet from another culture? Consider how results might change if compared against a Japanese diet (characterised by fish, seafoods, rice, vegetables, and soy) or an Indian diet (characterised by grains, dairy, vegetables, fruits, and fermented products).

# data[].attributes.body
Repeating the study

Incorporating diets from other cultures to have a more comprehensive comparison

Finding more participants for a larger sample size to confirm and expand findings

Perform subgroup analysis, to see if effects vary by biological sex, weight group, or any other metrics

Researching Microbiome Enhancer Diet as a framework for developing a diet for weight management strategies

Could help to inform methods by which to approach reducing global obesity

Elucidating how the gut microbiome and Microbiome Enhancer Diet affect each other

Determining specific mechanisms underlying delivery of dietary substrates to the gut microbiome

Targeting these mechanisms with personalised nutrition approaches

Optimizing energy balance + SCFA production through personalised diets

# data[].attributes.body
Under these inclusion criteria, there were 17 participants recruited, with baseline characteristics measured as follows:

# data[].attributes.body
Treatment 1: WD -> MBD (8 participants)

Treatment 2: MBD -> WD (9 participants)

# data[].attributes.body
Initial initial assessment period to establish outpatient dietary intake requirements. Free living & free-eating. This was to help establish a 'baseline' of what each patient's dietary habits were like, and how much energy intake they needed.

# data[].attributes.body
'Outpatient' phase:

Continued to live freely in the real world, but with all meals provided to them by the dedicated dietary team.

This was to help participants adapt to whatever diet group they were first assigned to, and to make sure that there were no immediate adverse effects caused by the food.

# data[].attributes.body
Inpatient phase:

Live in the metabolic ward for assigned diet #1. Diet, physical activity, sleep, and pretty much anything else you could think of were being monitored and controlled for. During this time, every stool passed was collected for analysis later down the line.

# data[].attributes.body
Return home: 14-day washout period

Before their second assigned diet, participants need to clear their system of the previous diet to ensure that the effects are not confounded. During this time, participants were specifically instructed to avoid alcohol, not consume caffeine within 72 hrs of inpatient admission, no artificial sweeteners, and no strenous physical activity 48 hrs prior to inpatient admission.

# data[].attributes.body
Inpatient phase:

Living in the metabolic ward for assigned diet #2. Similarly to the first inpatient phase, participants return for their second assigned diet. This is the 'crossover' part of the design.

# data[].attributes.body
Rationale: An indirect way to extrapolate the host metabolizable energy (which is the main purpose of the study!)

Benefits:

Affordable and simple measure

Measures electrons available to humans and microbes, thus being a proxy to quantify energy flow

# data[].attributes.body
Polyethylene glycol (PEG) is a nondigestible compound. Whatever enters via diet will thus be excreted.

# data[].attributes.body
For every participant, sample an amount of feces that is normalized to the amount of PEG excreted. In other words, this is a way to ensure that we are measuring the same amount of feces for each person, so any energy differences found can be attributed to the diet.

# data[].attributes.body
The fecal samples are exposed to a strong oxidazing agent, like Mn(III). A machine can then be used to measure how much Mn(III) was used up, and thus how many electron equivalents were available in the sample.

# data[].attributes.body
In the context of the study, then, it measures how much energy is still left in the feces. Thus, any energy left in the feces, means there is less energy available for the host!

# data[].attributes.body
A technique to identify the presence/absence of certain bacterial genera

Rationale: Used to compare the microbiome composition of participants between MBD vs. WD

# data[].attributes.body
On the collected fecal samples, sequence all the DNA using this technique that fragments the DNA and sequences all the reads in a high-throughput method. In the end, the reads are realigned. The advantage of this method is that it is can sequence a high amount of data in parallel, making the process very quick

# data[].attributes.body
A measure of diversity within a community, or rather the number of taxa contained within the fecal sample. Constructed via OTU classification and then analyzed using the 'microbiome' R package.

# data[].attributes.body
A measure of diversity between communities, or the differences in number of taxa between two different samples. In the context of the study, this means how different the MBD and WD diets are. This was measured using the Bray-Curtis dissimilarity metric and then plotted on a PCA plot for visualization.

# data[].attributes.body
Balance between the energy a host intakes and the energy expended

+ energy balance = energy intake > energy expended

- energy balance = energy intake < energy expended

We intake energy through consuming food and expend energy through metabolism

Hill O.J., et al. Endocrinology. 2013 Aug; 9(2): 111-115

# data[].attributes.body
Disruption of energy balance leads to cardiovascular and metabolic disorders(Blundell et al., 2015)

+ energy balance leads to detrimental effects

Obesity(our body stores the excess energy that we intake as fat)(Brown et al., 2016)

Insulin resistance leads to high blood sugar(Type II diabetes)(Ryan. D., 2020)

# data[].attributes.body
Energy that is taken up by the host through the intake of food

On the other hand:

Fecal energy is the energy that is lost through the feces

A higher fecal energy means that the host absorbed less energy from the food

Roberts S.B., et al. Advances in Nutrition. 2022 Aug; 13(6): 2681-2685

# data[].attributes.headline
Gut Microbiome is shown to modulate Metabolizable energy through diet

# data[].attributes.subject
Gut Microbiome is shown to modulate Metabolizable energy through diet

# data[].attributes.body
Diet that is high in fiber leads to more nutrients for bacteria

High-fiber diet is associated growth of beneficial bacteria like bacteriodetes and bifidobacteria

These bacteria allows for the fermentation of SCFAs(butyrate, propionate)

SCFAs that are produced influences the hosts ability to extract energy from food

Montenegro J., et al. Advances in Nutrition. 2023 Apr. 14(4): 840-857

# data[].attributes.body
Most of the previous studies done were pre-clinical trials therefore, there was a lack of human data

Could not conclude if a certain diet promoted growth of beneficial bacteria or if the certain bacteria was already present(lack of data on the composition of gut microbiome)

Studies Lack data on how the diet-gut interaction affects host metabolizable energy

# data[].attributes.attachment_caption
Nuciferine reduces the abundance of Firmicutes and increases the abundance of Bacteriodetes.  

# data[].attributes.headline
Changing the Gut microbiota composition ameliorates obesity(previous study)

# data[].attributes.subject
Changing the Gut microbiota composition ameliorates obesity(previous study)

# data[].attributes.body
Researchers in this study used Nuciferine(organic compound) which altered gut microbiota composition in mice

Nuciferine increased Bacteriodetes(SCFA producing bacteria) and decreased firmicutes

Nuciferine increased the composition of SCFAs producing bacteria, promoting SCFA production

This change prevented weight gain and fat accumulation in high fat diet mice

Limitation: Murine Study which is a clinical study

Wang Y., et al. Experimental Molecular Medicine. 2020 Dec; 13(1): 1-24

# data[].attributes.attachment_caption
The microbial diversity of Mice fed MD diet(red) and mice fed high fat high cholesterol(blue) and high fat low cholesterol(grey).

# data[].attributes.headline
A diet that is High in fat increases cholesterol and promotes metabolic syndromes(previous study)

# data[].attributes.subject
A diet that is High in fat increases cholesterol and promotes metabolic syndromes(previous study)

# data[].attributes.body
Researchers in this study fed mice with a high fat & high cholesterol diet(HFHC) and a Mediterranean diet(MD)

Found that HFHC diet decreases the composition of bifidobacterium and bacteriodetes as opposed to the MD

Decrease in these beneficial bacteria lead to increase in detrimental conjugated bile acids which potentially leads to Nonalcoholic fatty liver diesase(Metabolic Syndrome)

Limitations:

Could not conclude that diet(MD)-gut interaction rescued liver disease(Metabolic Syndrome) by increasing the composition of bifidobacterium and bacteriodetes(lack of data)

Zhang X., et al. Gut. 2021 Apr; 70(4): 761-774

# data[].attributes.headline
What were the Study Goals of this paper?

# data[].attributes.subject
What were the Study Goals of this paper?

# data[].attributes.body
Aimed to address the gaps in literature in other papers

To identify the changes in host metabolizable energy in response to different diets

To investigate the changes in microbiome composition due to different diets

# data[].attributes.attachment_link.title
Host-diet-gut microbiome interactions influence human energy balance: a randomized clinical trial - Nature Communications

# data[].attributes.attachment_link.description
The gut microbiome is causally linked to body weight in preclinical models. Here, in a controlled feeding study, the authors show that greater delivery of gut-microbiome fermentable dietary substrates to the colon leads to a net negative energy balance that is accompanied by robust microbial and host responses.

# data[].attributes.body
A diet that is rich in fiber leads to an increase of substrates that is available to the gut microbiome resulting in lower metabolizable energy(higher fecal energy)

# data[].attributes.attachment_caption
Fig 4a. Mean daily fecal weight from 6 days of composited feces averaged to generate daily production.

# data[].attributes.headline
Microbiome enhancer diet increased mean daily fecal weight

# data[].attributes.subject
Microbiome enhancer diet increased mean daily fecal weight

# data[].attributes.body
The MBD showed an increase in mean daily fecal weight compared to the WD.

# data[].attributes.headline
                                                            5                                                Integrating the key findings 

# data[].attributes.subject
                                                            5                                                Integrating the key findings 

# data[].attributes.body
We can conclude:

1. The microbiota profile that characterized the response to to MBD channeled more energy to the microbes instead of the host.

2. The increase in mean daily fecal weight supports the finding that there is increased biomass in feces through examining the fecal 16s rRNA gene copy number associated with each diet.

3. The microbiota composition differs between the MBD and WD diets.

4. MBD increased fecal and serum SCFAs indicating an increase in microbial fermentation.

# data[].attributes.body
Most previous studies were based on preclinical models, but this study provided strong evidence based on a highly controlled clinical trial.

Results from preclinical models suggested that more energy channelled to microbes would lead to more energy available to host

This study disproved that and demonstrated the opposite in clinical trials; that is, more energy channelled to microbes results in less energy was available to the host

Incorporated precise methodology and rigorous controls, especially with regard to the metabolic ward, that helped to determine causative results

This was lacking in many prior human clinical trials that aimed to study relationship between gut microbiome and energy loss

Relationship between gut microbiome and diet presents another angle to understand energy balance and weight management, which is important in finding solutions for obesity

Obesity is a very current and growing interest in health research as it is a significant risk factor for many chronic diseases that are leading causes of death, such as cardiovascular disease or atherosclerosis.