Studies Selection and Weighing for Suggestions

This is a part of an ongoing series of posts that are intended for microbiome testing labs, or those interested in starting one. I am downstream from all of the microbiome labs and will gladly work with any of them — my main concern is making people better — not the financial bottom line.

This post looks at issues involved with selecting studies to use for giving suggestions to consumers of microbiome result. These are questions that I have looked at and have made my own choices (a.k.a. technically trade secrets).

Method of microbiome detection used

There are three main types, listed below. Do you restrict to only one? Do you give a weight to different methods, for example the values suggested after each below?

For a discussion of the last two, see Comparison between 16S rRNA and shotgun sequencing data for the taxonomic characterization of the gut microbiota [2021]

Life Form/non-form that the study was done on

We have a wide variety of “bacteria incubators” reported in studies, including

  • Fish (Zebra fish especially)
  • Animals – which ones? Horses, Dogs, Cats, Cows, Pigs etc
  • Chemical Reactors simulating some living creature’s environment
  • Humans
    • Which ethnic groups
    • Location that the study was done (a proxy for diet) — different results from Mexico and Japan!
    • Age — children, adults and the elderly have different responses
    • Medical conditions in the cohort

Do you do a binary include/exclude or do you apply a weight to each?

Quality of Study

The following are commonly used in evaluating studies:

  • Read Beyond the Abstract – that means getting and reading the full study, including the appendix
  • Determine Whether All Results Were Included
  • Observational Study versus Randomized Controlled Trial
  • Odds Ratios and Confidence Intervals
  • Size of study

Do you give different weights based on the above? Some literature is below:

Interpreting Studies

Different studies report things differently. For example some may report the % change of a bacteria average, others may provide the actual distribution, others may just report that the control or the cohort average was higher with (P < 0.5). It is like trying to buy gas – one person is offering it by the gallon in US$, another in litres in Euro, a third “sufficient fuel to drive 200 miles in a 1958 Land Rover” for 3 oz of silver.

Method of Aggregation

Some studies use the Hartung–Knapp–Sidik–Jonkman random effects model [2021] to combine results. Other studies use DerSimonian-Laird method (cited by Cochrane) or The generic inverse variance outcome type in RevMan.

Bottom Line

I have my own magic in combining a multitude of studies and resolving the many many issues cited above. I encourage labs to do their own resolutions and then let people compare results (if they are in agreement, everyone should be happy). The real test is whether the suggestions work. So far, for my own experience and for a reasonable number of people that have provided feedback – they have. The suggestions may not be perfect, but my goal is to give suggestions that are more likely to help.

SIBO – Addressing Upstream Issues – Mouth

The recent article Quantitative sequencing clarifies the role of disruptor taxa, oral microbiota, and strict anaerobes in the human small-intestine microbiome [2021] identifies upstream as a maintainer of SIBO. A response to this post was people asking what to do This is not news for me, I have written about this over the last 7 years.

My short form would be to use Symbioflor-1 (to address sinus issues) and make sure that you rotate through different active ingredients in mouthwashes (and I would include my dad’s favorite: rinse your mouth with Scotch Whisky [or similar] – I will leave it to you if you spit out or not 🙂 ). I would suggest reading some of the above earlier posts.

Probiotics helping (or hurting) Probiotics

A while back I built a bacteria to bacteria interaction model with rich results. With the addition of the anti-modifier page for professionals, my mind went over to finding probiotic interactions. This is based on the 2000+ microbiome samples uploaded. I have the basic results below

The more positive, the Impact number the more it helps the other species. A negative number indicates that it will reduce the other. Thus, you should not take Clostridium butyricum and Akkermansia muciniphila together. If you are trying to increase Bifidobacterium bifidum then take Arthrobacter (in Prescript-Assist®/SBO Probiotic) and/or Lactobacillus paracasei.

You may wish to check my retail probiotic page to find out which products contains different species.

Take ThisTo Increase This
Akkermansia muciniphilaClostridium butyricum-6
ArthrobacterBifidobacterium bifidum21
ArthrobacterBifidobacterium catenulatum4
Bifidobacterium adolescentisBifidobacterium bifidum3
Bifidobacterium adolescentisBifidobacterium breve7
Bifidobacterium adolescentisLactobacillus fermentum8
Bifidobacterium adolescentisLactobacillus rhamnosus3
Bifidobacterium bifidumArthrobacter20
Bifidobacterium bifidumBifidobacterium adolescentis3
Bifidobacterium bifidumBifidobacterium catenulatum7
Bifidobacterium bifidumLactobacillus fermentum8
Bifidobacterium bifidumLactobacillus paracasei13
Bifidobacterium bifidumLactobacillus salivarius4
Bifidobacterium bifidumLactococcus lactis5
Bifidobacterium breveBifidobacterium adolescentis4
Bifidobacterium breveBifidobacterium longum13
Bifidobacterium breveLactobacillus crispatus9
Bifidobacterium breveLactobacillus rhamnosus6
Bifidobacterium catenulatumArthrobacter5
Bifidobacterium catenulatumBifidobacterium bifidum7
Bifidobacterium longumBifidobacterium breve18
Bifidobacterium longumLactobacillus fermentum3
Clostridium butyricumAkkermansia muciniphila-6
Lactobacillus crispatusBifidobacterium breve12
Lactobacillus crispatusLactobacillus rhamnosus7
Lactobacillus crispatusPediococcus6
Lactobacillus fermentumBifidobacterium adolescentis9
Lactobacillus fermentumBifidobacterium bifidum8
Lactobacillus fermentumBifidobacterium longum3
Lactobacillus paracaseiBifidobacterium bifidum12
Lactobacillus paracaseiLactobacillus plantarum4
Lactobacillus plantarumLactobacillus paracasei3
Lactobacillus plantarumLactobacillus rhamnosus3
Lactobacillus plantarumPediococcus3
Lactobacillus rhamnosusBifidobacterium adolescentis4
Lactobacillus rhamnosusBifidobacterium breve6
Lactobacillus rhamnosusLactobacillus crispatus9
Lactobacillus rhamnosusLactobacillus plantarum5
Lactobacillus salivariusBifidobacterium bifidum4
Lactobacillus salivariusPediococcus5
Lactococcus lactisBifidobacterium bifidum4
Leuconostoc mesenteroidesPediococcus3
PediococcusLactobacillus crispatus8
PediococcusLactobacillus plantarum4
PediococcusLactobacillus salivarius5
PediococcusLeuconostoc mesenteroides4

Increasing Akkermansia: Probiotics and Kampo

This is a personal observation post and not my traditional aggregation of studies. Your experience may differ.

Known Sources:

Akkermansia Probiotic

This is available exclusively as Pendulum Akkermansia. We signed up for the subscription plan when it was first announced, and they have kept shipping at their low introductory price every month. Within I week of getting the first shipment, I read a few posts that “it did not persist”. Excuse me, the typical turnaround time for a microbiome test is 3-4 weeks. I suspect that someone is gas-lighting. Or, they may have been taking a hostile probiotic at the same time.

We subscribed to only one bottle and we decided that the wife would take it for the first two months (we rotate probiotics). The results were her Akkermansia muciniphila went from 4,530 to 64,920 (91%ile) — so, it appears to have persisted (or helped the native ones to prosper by creating a friendlier environment). I should point out that that the fact that she has some to start with may be a significant factor for this awesome increase (that is, the environment was not totally hostile).

She noticed some significant changes, to her the most significant one was a major improvement in sleep.

Kampo (Japanese Name)

This is also known as fang feng tong sheng san (Chinese: also may be named: Fang Feng Tong Sheng Pian (Fang Feng Tong Sheng Wan,  防风通圣片) – best names to use on Amazon) or Bofu-tsusho-san. A professional user of Microbiome Prescription reported a major increase of Akkermansia with his patients using this and forwarded two studies that illustrated this.

  • Bofutsushosan improves gut barrier function with a bloom of Akkermansia muciniphila and improves glucose metabolism in mice with diet-induced obesity. [2020]
  • Increase of Akkermansia muciniphila by a Diet Containing Japanese Traditional Medicine Bofutsushosan in a Mouse Model of Non-Alcoholic Fatty Liver Disease [2020]
A massive bloom!
As an image

So, what else does Kampo do?

For additional studies, see pub-med.

Other Approaches

Current Experiment

As mentioned above, we rotate probiotics as a standard practice in our household. I am starting both the Akkermansia and Kampo and plan to do a new microbiome report in a month (so 2 months until this post gets updated). I expect a significant jump in my Akkermansia. At last test, it was 570 or 0.05% (via Biomesight), below the lower end of Dr. Jason Hawrelak Recommended ranges.


A 7 to 8 fold increase was seen after a month. The probiotic was stopped for a week before the sample was taken.

May be an image of text that says "Low High Description Bacteria Distribution (KM) BiomeSight (KM) 2021-10- 19 Self (family) Akkermansiaceae 16 Concern? Count BiomeSight 269847 글 Bacteria 2022-01- 24 Self (genus) Akkermansia Percentile 10 Distribution 570 269847 Count 署 Bacteria 34.7 (species) Akkermansia muciniphila Percentile 16 Distribution 570 4160 雪 199384 34.6 53.3 Bactena Distribution 570 4160 38.5 38 64.7 4160 55.9"
Using BiomeSight algorithm on FASTQ file
May be an image of text that says "Low Description iption High Bacteria Distribution (KM) Thryve (KM) 2021-09- 09 TEKNT (family)Akkermansiaceae 16 Concern? Thryve Count 269847 2022-01- 24 self (genus) Akkermansia Bacteria Percentile 10 Distribution 637 Count 269847 (species) Akkermansia muciniphila 言 Bacteria 35.8 Percentile 16 Distribution 637 4226 199384 言 Bacteria 35.7 53.4 Distribution 631 4276 64.8 39.4 4203 55.9"
Using Ombre algorithm on FASTQ file

As an unintended side-effect, a lost of 7+ kilos over 7 weeks without changing diet (or dieting)!!! I have also taken high dosages of bifidobacterium infantis with it. It is known to encourage akkermansia too.

Before/Donor/After FMT Analysis

A user of my site that is active consulting on autism microbiome manipulation obtained permissions for me to do an analysis of one of his patients going through FMT. All of the microbiome testing was done via Biomesight (including the donor). This is specific type of data that I have been pleading to see if we can make predictive models of what could occur with FMT.


I did analysis at the Species, Genus, Family, Order and Class level trying many many approaches. This summarize my key findings.

The second sample was done one month after the FMT. Patient was very good for a couple of days, then “the war started”. New more severe autism symptoms appeared.

Do NOT expect it to reduce overgrowths!

Looking at the lowest numbers of the recipient prior and the donor, we found that the post-FMT numbers had a clear pattern.

  • At the Class level, 97% was higher than the lowest of the two, 58% was higher than the highest
  • At the Order level, 96% was higher than the lowest of the two, 56% was higher than the highest
  • At the Family level, 95% was higher than the lowest of the two, 61% was higher than the highest
  • At the Genus level, 91% was higher than the lowest of the two, 51% was higher than the highest
  • At the Species level, 94% was higher than the lowest of the two, 47% was higher than the highest

This was shocking — 50% of the bacteria will be higher than either the donor’s or recipient’s levels. Many people will assume that the levels will magically average the two levels. The reality seen here is that only 50% of the time will the new level be between these two levels and 50%of the time it will be higher than either. This is unlikely to be a preferred outcome.

Unexpected Disappearances

There were several items where both the recipient and the donor had bacteria, they were gone in the post-FMT sample! This was not expected, of special interest is that Lactobacillus was wiped out.

  • Order: Puniceicoccales
  • Family: Clostridiales Family XVI. Incertae Sedis
  • Family: Lactobacillaceae
  • Family: Puniceicoccaceae
  • Genus: Alkalibacterium
  • Genus: Butyricimonas
  • Genus: Carboxydocella
  • Genus: Catonella
  • Genus: Lactobacillus
  • Genus: Macrococcus
  • Genus: Pelagicoccus
  • Genus: Turicibacter
  • Species: lingnae
  • Species: Streptococcus oralis
  • Species: Veillonella parvula
  • Species: Streptococcus pseudopneumoniae
  • Species: Carboxydocella ferrireducens
  • Species: Sutterella wadsworthensis
  • Species: Catonella morbi

Many New Kids showed up!

These are bacteria not seen in the recipient prior nor the donor sample

  • Class Level: Acidobacteria, Calditrichae,Chitinophagia,Flavobacteriia,Ktedonobacteria,
  • Order Level: Acidobacteriales, Calditrichales, Caulobacterales, Chitinophagales, Chroococcales, Desulfobacterales, Flavobacteriales, Kiloniellales, Nostocales, Oscillatoriales, Rhodocyclales, Rickettsiales, Streptosporangiales, Synechococcales, Syntrophobacterales, Thermogemmatisporales,
  • Family Level: Acetobacteraceae, Acidobacteriaceae, Anaplasmataceae, Calditrichaceae, Caulobacteraceae, Chitinophagaceae, Chroococcaceae, Clostridiales Family XII. Incertae Sedis, Cyanobacteriaceae, Cytophagaceae, Desulfobacteraceae, Dysgonamonadaceae, Flavobacteriaceae, Fusobacteriaceae, Hymenobacteraceae, Kiloniellaceae, Listeriaceae, Nostocaceae, Oceanospirillaceae, Oscillatoriaceae, Oxalobacteraceae, Prevotellaceae, Pseudanabaenaceae, Rhodanobacteraceae, Rhodocyclaceae, Rickettsiaceae, Rivulariaceae, Streptosporangiaceae, Synechococcaceae, Syntrophobacteraceae, Thermogemmatisporaceae, Thiotrichaceae, Verrucomicrobiaceae,
  • Genus Level: Acholeplasma, Acidaminobacter, Aminobacterium, Ammonifex, Anoxybacillus, Asticcacaulis, Bilophila, Caldithrix, Calothrix, Catenibacterium, Chroococcus, Cyanobacterium, Desulfofrigus, Desulfosporosinus, Dokdonella, Dysgonomonas, Edaphobacter, Ehrlichia, Emticicia, Escherichia, Fusibacter, Fusobacterium, Gillisia, Haemophilus, Insolitispirillum, Kushneria, Listeria, Luteibacter, Lysinibacillus, Marinospirillum, Microbacterium, Neisseria, Niastella, Novispirillum, Oleomonas, Olivibacter, Oscillatoria, Parapedobacter, Paraprevotella, Pelotomaculum, Pontibacter, Ralstonia, Rickettsia, Roseomonas, Sarcina, Sebaldella, Skermanella, Tepidanaerobacter, Tepidimicrobium, Thalassospira, Thermoanaerobacter, Thermogemmatispora, Thiothrix,
  • I will skip the species level…

Bottom line is that the microbiome has become much more diverse

Recent FMT aspects

FMT destabilizes the microbiome, there are “strain riots” in the guts. We can see this with all of the “New Kids” showing up because the existing occupants are busy dealing with each other. This can be seen by the post microbiome having a lot more taxonomical items (550 vs 374 before – a 47% increase), The microbiome, over time, will downsize and stabilize with a new normal. During this period, you want to entrench your desired items by feeding it the right things and avoiding the wrong thing.

Personally, I would suggest a new sample every 6 weeks to monitor the stabilization.

Is FMT Worth the Risk?

FMT is effectively an organ transplant. Like organ transplants, there are significant risks of rejection and no way to undo it once it happens. From correspondence with many people who have tried it for ME/CFS, my feelings are that it is not a magic bullet. It is closer to playing Russian roulette, but with 5 of the 6 bullet chambers having bullets in the chambers.

I just spent 90 minutes zooming to the consultant involved with this autistic child. We both agreed that FMT for autistic children is not a wise course. The consultant is scratching their head on what to help this child recover from this situation.

Some prior posts on FMT

Hydration and the Microbiome

If you are dehydrated you will typically see a change of stools. Seeing hard pebbles and dry stools is a logical consequence of the body rationing water. Recently, we got a new smart scale ($30 on Amazon) that comes with a smart phone app and does multiple measures, including hydration. I have been running below the desired range, so I am busy hydrating with Gerolsteiner Mineral Water (from Traders Joe) etc.

Conceptually, the availability of water should impact the microbiome. So tonight I started to search out studies to confirm my speculation.

Effect of Increased Daily Water Intake and Hydration on Health in Japanese Adults, 2020

There were five out of the 108 types of intestinal bacterium at the genus level that showed significant differences within and between groups due to water supplementation, and 17 out of 564 species identified by the homology search of OTU representative sequences in the DDBJ 16S database showed the same behavior… Of these, a slight correlation was seen in the intervention group between changes in blood pressure and changes in the Psudoflavonifractor capillosus bacterial count (R = 0.42) Kineothrix sp. (R = 0.36), Feacalibacterium prausnitzii (R = 0.38), and Ruminococcaceae (R = 0.34) showed weak correlations between changes in body temperature and changes in bacterial count

Some related studies that implies impact on the microbiome but failed to do microbiome analysis with the study

Dehydration is often reported as a contributor to various conditions

Bottom Line

Hydration is an often overlooked aspect of improving the microbiome. It has impacts on blood pressure, body temperature, mood and cognitive ability. While we have few studies on it’s microbiome impact, we can likely assume safely that improved hydration will improve the microbiome. It should not be left to a “I drink enough water, I do not feel dehydrated”, but with actual measurements. Improving it is actually a slow process — my goal is to shift from my current level below, to at least 55%.

Revisions of Symptom Entry and Management

I just pushed an update that included features requested by a reader. The main items are:

  • Ability to enter symptoms when you do a test (“Pending Sample”)
  • Ability to copy symptoms from one sample to another
  • Ability to delete all symptoms for a sample with one click
  • Generation of a short list of possible symptoms from your bacteria

All of these options are shown for each sample via the dropdown:

Entering Symptoms

This has had one minor change, a new choice appears, “Pending Sample”. It allows you to enter symptoms when you do the sample (instead of trying to remember them 4 weeks later). Also two buttons are added to make status easier. Remember to use the Search box to filter

using Search
Clicking [Show All Items]

Clicking [Show Picked Items]

Quick Symptoms Additions

This takes your forecast symptoms with sufficient significance, removes any symptoms already entered, then show symptoms to consider.

If you check a few and click [Add]

These items will disappear from this list.

Symptoms Management

This allows you to copy symptoms between samples (for example, the same sample may be processed by multiple labs). Just select the sample you wish to copy from and click [Copy]

If you realized that you made a mistake, you do not have to uncheck item by item. you can single click all of the items.


The algorithm for predicting symptoms has been revised (hopefully improved). There may be a further change, have some complex modelling to add. Also the ability to change from sample to sample has been added

From Bacteria prediction
From Consensus Report

Colonoscopy prep may be a blessing

A reader mentioned getting scheduled for one. Coincidentally, a week ago, I had a natural clearing out of the bowels (source unknown). I suspect that both scenario may produce the same opportunity to do some restructuring.

The first item to be aware of, gravity, bacteria further up the flow will repopulate (for better or worst). For myself, once it became clear that the bowels were being deeply emptied, I loaded up on herbs that impact many of the bad bacteria for a day (several capsules of each, several times a day).

The rationale was to thin out the bacteria that are up-channel.

I then started to repopulate, the first item, an E.Coli probiotic, symbioflor 2 e.coli probiotics, stopped the natural clearing within 2 hrs (not surprising given what made Mutaflor, the alternative E.Coli probiotic, famous back in 1918). I then proceeded to load up on only probiotics that are known to persist (see thus post, Studies on Probiotic Persistence). For myself, I noticed some improvements (but really I do not have much wrong to improve).

This simple approach conceptually should work with colonoscopy prep. If moviprep (prescription)  is being used, we have a pretty good profile on it’s impact from BMJ’s Effects of bowel cleansing on the intestinal microbiota

That’s it — seize the opportunity!

Which brand of Herbs? A reader asked

Long ago we changed over to making our own pills/capsules using Organic Bulk Purchases. It has the following benefits:

  • Much lower cost per capsules
  • It is organic ingredients
  • Often you can also make tea from it (depends if it is powdered or not)
  • No fillers or creative mixology from brands.

A few examples

Organic India Triphala Powder - Immune Support, Digestion, Adaptogen, Colon Cleanse, Nutrient Dense, Vegan, Gluten-Free, Kosher, USDA Certified Organic, Non-GMO, Triphala Powder Organic - 1 Lb Bag
454 g for $16, versus 41 g for $15 as retail capsules
220 g for $7 versus 90 g for $19.00 as prepared capsules

One Readers Feedback

The experiment was an abject failure, unfortunately. 
I cleared the bowels and took no action the day of colonoscopy (Monday), other than to eat a dinner that included some fermentable fiber veggies. 
The next day (Tuesday) I took the baby scoop of Custom Probiotics D Lactate Free, which includes l rhamnosus. Continued eating meats and fermentable fiber veggies, introducing some shitaakes.
SIBO symptoms roared back with a vengeance that seemed almost too fast to be possible. By Tuesday night I had gross SIBO burps and an upset tummy. 
Wednesday I took a heaping baby spoonful of d-lactate free probiotics and suffered even more upset. By Thursday I forewent the probiotics but continued eating fermentable fibers, with a violent, burning, smelly bowel clearing that evening. I also became uncharacteristically emotionally reactive. 

Felt better Friday and switched to non-fermentable fibers. I had an mHBOT session that typically “resets” me, but after a low-fermentable fiber dinner, I got hit with a wave of brain fog I haven’t had for some time since doing rifaximin in Sept, continuing HBOT, and taking continued boswellia and Atrantil. 
I fogged out again after my morning Americano today, which is usually fine. Having unhappy poops again. A bit frustrated—I seem to have sent myself in the wrong direction and don’t totally understand why. I’ll add theanine for mast-cell control and start neem. Considering a rifaximin round. 
One theory—I have high mycophenolic acid in urine, and noted rats without microbiome do better when inundated with mycophenolic acid. Wonder if this is an angle to explore. 
Anyway! I thought you may be interested in the results—hope this wasn’t an overshare! I figure we’re all learning together.  

My comment: It is clear that the clearing set things up for a change – unfortunately, it went in the wrong direction. One of the items that I cited, “load up on only probiotics that are known to persist (see thus post, Studies on Probiotic Persistence).” was not done — Custom Probiotics D Lactate Free is not known to persist.

Producers of Butyrate, D-Lactic Acid and Histamines

These are often asked for with people often running off old research. Often the research is based on seeing an increase of one of these when a specific bacteria increase… hence. this bacteria must be producing it! This was the best that we could do from old, last millennium technology and lab tests. We have enter a new world that is summarized on Kyoto Encyclopedia of Genes and Genomes. Instead of measuring substances (never with a pure culture of a specific bacteria), we can look at the gene in each bacteria and what they produce. In other words, we can get more accurate information that is truly bacteria specific.

These pages list the enzymes that produces it, for example         2.3.1.- We can then look to see if the enzyme consumes (substrate) or produces it. This CONSUMES histamine this PRODUCES histamine

Then it is just a matter of looking up which bacteria has these enzymes!

Specific Species and Strains

The three files below are directly from KEGG data

Genus of the producers

Unfortunately, no lab detects all of these strains and often report “unknown Species in Some Genus“. I have seen that being as high as 45% not being identified in some samples. A work around is to look at the genus numbers — which are usually pretty complete for most labs. This is a two sided coin, because some members of a genus may be a producer and some may not be. We do not know the ratio for a genus between these two. This approach will identify potential candidates, but not definite candidates… more fuzzy logic.

Bottom Line

All of this information is freely available on Kyoto Encyclopedia of Genes and Genomes, it just take diligence to extract and assemble it. If you see items on a labs reporting that is NOT on these lists, challenge the lab to produce evidence. I suspect most labs will produce studies with circumstantial evidence only, “because crime goes up when this ethnic group moves in — it must be that ethnic group” — ignoring that a different ethnic group may be behind it. An example of a drug problem in one city at one time. Most of the drug dealers were African-Americans, but the importers were Vietnamese. With KEGG, we are looking for the fingerprints on the gun or drug packages intercepted,

IBS/SIBO/Constipation etc etc etc

A reader requested an education analysis using the tool at Microbiome Prescription.

Back story-long history of gut issues/IBS.Terrible time post partum 22 years ago with sleep issues  and mental health. I’ve been down the hell hole of modern medicine on all kinds of meds for years. Finally diagnosed with SIBO in 2019 and then no luck with treatment. More recently had bad reaction to high doses of Vitamin D-gut issues worse- total body pain, inflammation,  food intolerances,  terrible insomnia. I will add-horrific constipation not resolved unless I take herbal formulas [Microbe Formulas  Bowel Mover and Dr. Christophers Lower Bowel Formula. I try to rotate. No specific order. I do think the garlic in the Microbe formulas does help.]

She also mentioned mold and Lyme markets. From Citizen Science we have Comorbid: Mold Sensitivity / Exposure and Infection: Lyme. I will do those separate at the bottom.

I am going to do layers of suggestion and see what evolves. We start with Dr. Jason Hawrelak criteria for a healthy gut. We find a lot of issues as shown below

TaxonomyRankLowHighYour ValueStatus
Bacteroidiaclass03561.543Not Ideal
Akkermansiagenus130.005Not Ideal
Bacteroidesgenus02058.983Not Ideal
Bifidobacteriumgenus2.550.014Not Ideal
Lactobacillusgenus0.0110.005Not Ideal
Methanobrevibactergenus0.00010.020Not Ideal
Roseburiagenus5100.795Not Ideal
Proteobacteriaphylum045.34Not Ideal
Bilophila wadsworthiaspecies00.251.08Not Ideal
Escherichia colispecies00.010.047Not Ideal
Faecalibacterium prausnitziispecies10150Not Ideal

The key suggestions computed by the AI are shown below. We will add more suggestions and end up with a consensus report joining all of these set of suggestions into a single report

A second approach is not to limit to a few key items, instead look for odd items across all bacteria. We use Kaltoft-Moltrup Ranges and get the following bacteria being identified:

Bacteria NameAnalysis
  BacteroidaceaeToo High
  BacteroidesToo High
  Bacteroides caccaeToo Low
  Bacteroides gallinarumToo Low
  Bacteroides paurosaccharolyticusToo High
  Bacteroides thetaiotaomicronToo High
  biotaToo Low
  Blautia hydrogenotrophicaToo Low
  CatonellaToo Low
  Catonella morbiToo Low
  ErysipelothrixToo High
  Erysipelothrix murisToo High
  FaecalibacteriumToo Low
  LactobacillaceaeToo Low
  Parabacteroides distasonisToo Low
  RuminococcaceaeToo Low
Many of these are common with IBS
Suggestions generated

Our third pass, is using US National Library of Medicine studies that identify certain bacteria associated with IBS. We will use IBS but widen the criteria used to extreme 6%. Some of the bacteria are cited above, and some are new.

Bacteria NameAnalysis
  BacillusToo Low
  BacteroidaceaeToo High
  BacteroidesToo High
  Bacteroides ovatusToo High
  Bacteroides thetaiotaomicronToo High
  Bacteroides uniformisToo Low
  Bacteroides vulgatusToo High
  ClostridiumToo High
  DesulfovibrioToo Low
  Dialister invisusToo High
  EnterococcusToo Low
  FaecalibacteriumToo Low
  RuminococcaceaeToo Low

We notice that   soy,  Cacao and  lactobacillus casei (probiotics) seem to be included every time, although we have different bacteria being selected.

Going over to citizen science, we see four matches for SIBO

Bacteria NameAnalysis
  Escherichia albertiiToo High
  PaenibacillusToo Low
  Serratia entomophilaToo High
  Symbiobacterium toebii Rhee et al. 2002Too Low

Unfortunately the information we have for this is very limited.

Going back to US National Library of Medicine for SIBO, we get NO BACTERIA matches at all. My conclusion is that it may be atypical SIBO.

At this point, I want to check some specific items that she cited. There is a tool for that

  • For Vitamin D, we appear to have adverse effects
    • Categoric Sum:1
    • Categoric Average:0.1
    • Log(Count) Sum:-8.4
    • Log(Count) Avg:-0.6
  • For Garlic, we have a definite positive effect
    • Categoric Sum:3
    • Categoric Average:0.3
    • Log(Count) Sum:7.4
    • Log(Count) Avg:0.8

These predictions are solely from the microbiome and agree with what she has experienced.

Some Predictions

Above tested two substances that had been tried and the prediction appear to agreed with her experience. She asked about an items she was planning to take or recently started.

  • lactoferrin – which does not match any item, I selected iron and the results suggested that it will not improve matters. This looks at all undesired shifts.
    • Categoric Sum:0
    • Categoric Average:0
    • Log(Count) Sum:-10
    • Log(Count) Avg:-0.8

I also check the merge consensus report (see bottom) where we are selecting only the bacteria of concern. It is also an avoid

Consensus Report

Each of the above list of suggestions are stored on the server (for 24 hours) and we can see all of them together.

Our top suggestions (i.e. items that moves everything above in the right direction without exceptions)

Safest Takes

The complete list is below for the person to explore in more details. There are 400+ items that have good or bad impact.

My non-medical profession selection would be the following as shown below, using dosages from clinical studies,

resveratrol (grape seed/polyphenols/red wine)2000   mg/d
soy20 gm/day
Cacao2000   mg/day
barley60 gm/day
lactobacillus casei (probiotics)48000   MCFU/day
(48 BCFU)
fructo-oligosaccharides (prebiotic)15 gm/day
walnuts75 gm/day
folic acid,(supplement Vitamin B9)5   mg/day
N-Acetyl Cysteine (NAC), 2400   mg/day
vitamin b3 (niacin)1000 mg/day
lactobacillus reuteri (probiotics)5 MCFU

As always, this is produced from a computer AI model and not clinical experience. Before any change is done, it should be discussed with your medical professional. Some items, like 1000 mg of niacin per day may require testing (see this summary on niacin from the National Institute of Health)

Mold and Lyme Markers

Lyme is always a fuzzy area –if the person had ever had EBV and their microbiome is off, then false positives are well reported in the literature.

Mold Sensitivity
Lyme associated

The suggestions are shown below, there are a few matches with the above

Safest Take

I did a side by side comparison and found that there was a lot of disagreement between the sets of suggestions. That is not unexpected, because the bacteria selected determines the suggestions.

My gut feeling is that the IBS/SIBO is the preferred one — the citizen science did not have a single item auto checked, I had to go with the secondary items 💡 to get suggestions. This implies a weak match. Second, the IBS/SIBO included the gold standard bacteria identified from formal clinical studies. In short, likely better quality of information.

For those that are interested in how I created the above comparison, see this video — just change the URL to Source and enter a name in the column before pasting between sheets.