Is there a SIBO diet?

I was messaged

Ken, I read so much of your stuff, I have ZME 39 years. My granddaughter has POTS and now she was diagnosed with SIBO and fructose Intolerance. Could you point us to a diet for SIBO; She has not been given one nor can find it. I thought of you right away, Please help. Have a great weekend, holiday.

What has been actually studied

First, the reality of SIBO diagnosis. IMHO, it tends to be a little “hit and miss“.

Although abdominal bloating, gas, distension, and diarrhea are common symptoms, they do not predict positive diagnosis. Predisposing factors include proton-pump inhibitors, opioids, gastric bypass, colectomy, and dysmotility. Small bowel aspirate/culture with growth of 10-10 cfu/mL is generally accepted as the “best diagnostic method,” but it is invasive. Glucose or lactulose breath testing is noninvasive but an indirect method that requires further standardization and validation for SIBO. Treatment, usually with antibiotics, aims to provide symptom relief through eradication of bacteria in the small intestine. Limited numbers of controlled studies have shown systemic antibiotics (norfloxacin and metronidazole) to be efficacious. However, 15 studies have shown rifaximin, a nonsystemic antibiotic, to be effective against SIBO and well tolerated. Through improved awareness and scientific rigor, the SIBO landscape is poised for transformation.

Small Intestinal Bacterial Overgrowth: Clinical Features and Therapeutic Management [2010]

There are dozen of diets pushed by influencers for diverse reasons. I tend to be a “show me the clinical studies or reviews” type. What do we find is…

This narrative review suggested that there is a favorable association with monoprobiotics, fiber supplementation and mindful eating, and negative effects associated with low-FODMAP diets on the gut microbiome, especially in IBS patients. Applying these recommendations to the treatment of SIBO was inconclusive due to a lack of research including SIBO patients in the studies. 

Efficacy of an Irritable Bowel Syndrome Diet in the Treatment of Small Intestinal Bacterial Overgrowth: A Narrative Review [2022]

Our findings suggest preliminary evidence for a role of alternative therapies in the treatment of SIBO. However, robust clinical trials are generally lacking. Existing studies tend to be small and lack standardized formulations of treatment. Breath testing protocols and clinical symptom measurement greatly varied between studies. Large-scale, randomized, placebo-controlled trials are needed to further evaluate the best way to utilize alternative therapies in the treatment of SIBO.

Alternative Treatment Approaches to Small Intestinal Bacterial Overgrowth: A Systematic Review [2021]

Where do we go from here?

My inclination is to encourage a suitable microbiome test (OmbreLabs, Thorne or Biomesight.com [discount code: Micro] and use the Microbiome Prescription site. There is an apriori set of suggestions based on the bacteria reported from studies. It is interesting to note that rifampicin antibiotic is suggested which is closely related to rifaximin which is cited in the study above, suggesting that working from the microbiome data is a reasonable approach. Other diet related items computed are:

  • aspartame(sweetner)
  • bifidobacterium adolescentis,(probiotics) 12BCFU/day
  • carob
  • catecholamines(polyphenol)
  • e.coli probiotics (Mutaflor, Symbioflor-2)
  • dairy / lactose /lactulose
  • d-ribose 10gram/day
  • fat in diet
  • fluorine (i.e. in toothpaste!)
  • fruit/legume fibre
  • grape polyphenols
  • green-lipped mussel
  • iron 400mg/day
  • ku ding cha tea
  • mannooligosaccharide(prebiotic) 8gram/day
  • Miso
  • navy bean
  • non-starch polysaccharides
  • oligosaccharides(prebiotic)
  • proton-pump inhibitors(prescription) 60mg/day
  • Pulses
  • raffinose(sugar beet)
  • red alga Laurencia tristicha
  • red wine 250ml/day
  • rice bran
  • sodium butyrate
  • Sriracha sauce
  • ß-glucan 500mg/day, converting to foods:
    • Mushrooms, especially shiitake, maitake, reishi, shimeji and oyster varieties
    • Date fruit, a sweet and fiber-rich fruit native to the Middle East
    • Oats, a cereal grain that can help lower cholesterol levels
    • Barley, one of the highest-fiber grains
    • Seaweed, a marine algae that contains various nutrients and antioxidants
    • Rye bread, a type of bread made from rye flour [Sources of Beta-Glucan (weekand.com)]

Do just the items that you tolerate (physically, philosophically), there is not a need to do all.

Items to AVOID include:

  • cinnamon (oil.spice)
  • foeniculumvulgare,fennel
  • lactobacillus plantarum(probiotics)
  • oregano(origanum vulgare, oil) |
  • syzygiumaromaticum(clove)
  • thyme(thymol, thyme oil)
  • triphala

I would extend it to all lactobacillus probiotics because there are hostile to E.Coli probiotics.

Bottom Line

Working from an individual microbiome is the best way to proceed (IMHO). There are massive issues with both being sure of the SIBO diagnosis being correct AND no clinical evidence (except for antibiotics use) of any specific diet being useful.


New Feature to hunt cause of symptoms

Over the last week I have been working on Exploration: Salicylate Sensitivity And the Microbiome with some success. I rolled one analysis feature into a new page that may give scents as to causes.

The basis is that we look for bacteria that are seen more or less often than expected. Bacteria distribution is not a bell curve/normal distribution which makes the use of averages very suspect. Checking against frequency side-steps this answer.

Direct Link: MicrobiomePrescription : Abnormal Frequency of Bacteria for Symptoms

You can select the lab source and up to two symptoms.

There may be no data (if there is not sufficient data) for some single symptoms or symptom combinations.

Why are the Bacteria Names Different?

This is because there are no standardization of reading 16s Data Files (FastQ). See The taxonomy nightmare before Christmas…

Explore and share any interesting discoveries….

You can even see some shifts with age!

If there is sufficient data to hazard suggestions a red button will appear at the bottom:

This report indicate the experimental nature of the report and the lack of data on many bacteria.

Updates on PDF Reports for Professionals

This is an update on this earlier post. New Reports for Medical Professionals
There has been two additions:

  • Retail Probiotics are listed (if there are any!)
  • Uber Consensus now has the ability to generate a PDF
    • This is particularly for people that used Ombre and then had the FastQ files processed by Biomesight.

Probiotics Example

These are only the completely safe ones that will have some benefits. There may be none reported.

Uber Consensus

When you view the consensus, you can then get the report

One word of warning: the bacteria list may be massive — especially when different labs are involved.

For the sample below — it is FIVE pages.

Sample113258251_239512483_241239419-Naturopath-1Download

Comparing standalone suggestions.

I would be interested to see how the three separate consensus suggestions compare (i.e. not doing the uber consensus). Do the top takes & avoids match across the different labs, or are they different? Because if they are different then the algorithm is not robust to changes in lab.

Request from a reader.

This is a part of this series of post:

Using the same data, the process that I will use is where items suggested in both are the same (i.e. take or avoid) or different recommendations. In pseudo sql: 

Select Percent(A.Take=B.Take) from Suggestions1 A Join Suggestions2 B on A.substance=B.substance

The results actually surprised me!

Lab ComparisonItemsAgreementAvg Difference
Ombre vs Biomesight1705100%52
Ombre vs Thorne1706100%100
Biomesight vs Thorne1694100%54

My expectation was somewhere between 80-90%, the same range that I got doing cross validation. The Priority and weight are different, but the take or avoid decision are the same. The difference between these pseudo values was also calculated and added to the table above. Magic Soy on Ombre may be 430, on Thorne 330, on Biomesight 530.

Conclusion, the algorithm is more robust than I expected!

Caveat: This was done using “Just give me suggestions” collection of algorithm on each lab’s data. Disagreements are definitely expected when bacteria selection are “over-focused” and not including the holistic picture of the microbiome.

Microbiome Prescription Uber-Consensus Analysis – Excellent

This is part 2D of Comparing Microbiomes from Three Different Providers – Part 1. I decided to do each lab separately and then do an overview at the end. See also

In this post we are going to combine all of the consensus from the above 3 different sample reports and see what is shared by all of the suggestions. The goal is to see whether there is come convergence of suggestions.

Uber Consensus

We select the Multiple Samples tab and then check the three consensus reports. We should note the number of modifiers in each sample suggestions (over 6000 items were consider). This on the surface appears to be at least one, if not two magnitudes more than the suggestions from the labs,

The following are selecting the highest positive or negative entries where there is good agreement.

SubstanceTakeAvoidPriority
melatonin supplement111289
l-glutamine91201
Conjugated Linoleic Acid110-197
high animal protein diet101207
low carbohydrate diet101162
low-fat high-complex carbohydrate diet101152
animal-based diet110-237
dietary fiber110-311
fibre-rich macrobiotic ma-pi 2 diet012-172
Hesperidin (polyphenol)111295
luteolin (flavonoid)111293
Arbutin (polyphenol)111284
diosmin,(polyphenol)111284
cranberry (flour, polyphenols)101210
Fisetin19-202
Caffeine111252
Burdock Root012-471
pea (fiber, protein)012-318
barley,oat110-253
wheat bran111-244
Pulses111-217
sunflower oil012-195
gallate (food additive)110174
gallic acid (food additive)012-174
mastic gum (prebiotic)90206
inulin (prebiotic)111-397
arabinogalactan (prebiotic)111-359
resistant starch111-243
lactobacillus plantarum (probiotics)012-352
saccharomyces boulardii (probiotics)110-296
lactobacillus rhamnosus gg (probiotics)111-294
bifidobacterium longum (probiotics)110-200
Vitamin B-1,thiamine hydrochloride111308
retinoic acid,(Vitamin A derivative)111284
Vitamin B-6,pyridoxine hydrochloride111284
Vitamin C (ascorbic acid)111283
vitamin B-7, biotin111270
Vitamin B-12111259
vitamin B-3,niacin111229

Commentary

There were no probiotics in the above to take, only those to avoid. Interesting that the labs whose business model includes selling probiotics actually suggested these probiotics (ones to be avoided above)!! This have a strong aroma of conflict of interests.

Many of the above items were not suggested by any lab despite a few being typical — i.e. melatonin.

Other Observations

Percentages of Percentiles

For BiomeSight and Ombre, we compute percentiles based on samples uploaded. Thorne provides their own percentiles. We see a major contrast below.

MeasureBiomeSightOmbreThorne
Jason Hawrelak8 ideal (96%ile)6 ideal (75%ile)5 ideal (56%ile)
Bacteria Reported7488863349
Shannon Diversity Index:1.93 (89%ile)3.34 (93%ile)2.85 (70%ile)
Simpson Diversity Index: 0.2 (8%ile)0.2 (5%ile)0.3 (9%ile)
Chao1 Index :17785 (89%ile)33700 (89%ile)341848 (70%ile)
The numbers are using based on the lab population

Bottom Line

The purpose of this series of post was to do a non-judgmental evaluation of the three lab reports and suggestions to help people make better choices. All of the steps that I did is very repeatable by anyone who wish to replicate this experiment. (P.S. If you do, I am not opposed to do a repeat set of posts with different data).

  • Key findings:
    • Only Biomesight provided AVOID lists (too short IMHO) — i.e. they are happy for you to keep feeding ‘bad’ bacteria
    • Only Biomesight provide studies links connected to their suggestions
    • The report from each lab are significantly different, however when that report is used with Microbiome Prescription algorithms, we get agreement. This is likely due to the nature of the algorithms used.

My impression is to use whichever lab is available to you (two sell in the US only, one world wide); ignore their suggestions and use the free suggestion engine on Microbiome Prescription.

Microbiome Prescription does provide detail evidence trail on every single suggestion it makes. Some of the evidence is less than ideal, but it is at least reasonable (and less than ideal data is diminished in weight).

I gave this an Excellent because it matched the criteria that I use:

  • Avoid lists are given
  • Evidence trail to studies for every suggestion
  • A large number of substances are evaluated
  • Weights are given for Take lists.

(And I acknowledge there is a conflict of interests here — but no financial gain).

The following videos illustrate the process to see the evidence trail.

Thorne Suggestions Analysis – INCOMPLETE / FAILED

This is part 2C of Comparing Microbiomes from Three Different Providers – Part 1. I decided to do each lab separately and then do an overview at the end. See also

Process

It is very simple, look at their suggestions, look at any references they provided. Then look at Microbiome Prescription evidence trail for the same substances.

Suggestions

The number of suggestions were very few. They are listed below. None of the suggestions had links to studies supporting them.

  • Follow a ketogenic or low-carbohydrate diet
  • Avoid eating habits that interfere with sleep
  • Product Recommendations
    • Dipan-9®: Pancreatin
    • Effusio® Prebiotic+
      • Blueberry
      • Green Tea
      • Pomegranate
      • Xylitol
      • Stevia
    • FloraMend Prime Probiotic® 
      • L. Gasseri KS-13
      • B. Longum MM-2
      • B. Bifidum G9-1
    • Undecylenic Acid – 10-Undecenoic Acid
  • Vitamins were:
    • Red: Vitamin B3, B12
    • Orange: Vitamin B6,B9
  • All probiotics were GREEN.

There was no scientific literature links provided to support these choices.

How do suggestions compare?

Analysis against Microbiome Prescription using the data they reported.

  • Vitamin B3: take 3, avoid 1
  • Vitamin B6: take 3, avoid 1
  • Vitamin B9: take 3, avoid 1
  • Vitamin B12, take 3, avoid 1
  • L. Gasseri: take 1, avoid 3
  • B. Longum: take 0, avoid 3
  • B. Bifidum: take 0, avoid 4
  • Blueberry: take 3, avoid 1
  • Green Tea: take 2, avoid 2
  • Pomegranate: take 1, avoid 3
  • Xylitol: take 2, avoid 1
  • Stevia: take 0, avoid 4
  • Pancreatin: take 1, avoid 0
  • ketogenic: take 1, avoid 3
  • low-carbohydrate diet: take 2, avoid 1

Undecylenic are in Microbiome Prescription database. Undecylenic has nothing on PubMed dealing with the microbiome that I could locate.

My Impression are:

  • For the 4 B-vitamins we have agreement.
  • For everything else, we have so-so agreement. In fact, the agreement is the same that you would expect with flipping a coin (random)
  • We have very few suggestions of what to take
  • We have no clear suggestions on what to avoid (beyond “other diet” types).

Bottom Line

Thorne gives almost no suggestions. There is no links to study supporting their suggestion. The suggestions seem to be ultra-safe suggestions that should work for most people. It if very questionable if the bacteria results were used for the suggestions.

As an ex-teacher, I would not give a grade, I would give an INCOMPLETE-FAILED, nothing of significance submitted. No real effort made.

The videos below shows how you can see the evidence for the suggestions on Microbiome Prescription.

Biomesight Suggestions Analysis – Good Results

This is part 2B of Comparing Microbiomes from Three Different Providers – Part 1. I decided to do each lab separately and then do an overview at the end. See also

Process

It is very simple, look at their suggestions, look at any references they provided. Then look at Microbiome Prescription evidence trail for the same substances. My usual “Just the facts, ma’am” approach. This data was retrieved on 24 Aug 2023.

First item, the suggestions are far wider and deeper than Ombre. With Rosemary and Rosemary extract being separate!

Clicking one the green bar describes the why with links to research.

Unfortunately the research suggestions appears to be second generation. For example, when I clicked on Bifidobacterium, I see that Chickpeas are transformed to Galactooligosaccharides (GOS) which is reasonably correct with a risk of over simplification.

“The galacto-oligosaccharides (GOSs) naturally occur in legumes such as lentils, chickpeas, and beans.”[2016]

Chickpeas, lentils and beans contain other substances. A First generation reference would explicitly cite chickpeas. A second generation would cite a component that is significant in chickpeas(with fingers crossed that other components will not have an adverse effect).

This same process is done for Pre-biotics & Ingredients, Probiotics and LifeStyle

Items to avoid are shown in red (sometimes there are none). The “orange” color appears to be me to be more a yellow (to my eyes).

Supplements – Ugh

My preference is to name the explicit supplements to take (and to avoid) and have the user find a product somewhere. Biomesight provides the product name (which can be ordered thru them) and below the product list the whys. From the time it takes this page to render, I surmise they are computing them upon request

Spot checking the very first item, we see the ingrediants:

  • Galactooligosaccharides (Bimuno®)
  • Organic gold and green kiwifruit powder (Livaux® and ACTAZIN®)
  • Organic Xylooligosaccharides (PreticX®)

How do suggestions compare?

Microbiome Prescription tries to use first generation citations, BiomeSight appears to often use second generation citations [Ombre appears to use halogenic citations]. The ones that I checked are good as second generation citations.

Below are the take suggestions from Biomesight and what Microbiome Prescription consensus suggests. I skipped foods to minimize second generation citation issues.

SubstanceMP TakeMP Avoid
resveratrol40
Galactooligosaccharides40
pectin13
xylooligosaccharides03
quercetin40
ShenLing BaiZhu San13
acacia fiber––
Arabinogalactan04
lactose (not in lactose intolerant)30
milk oligosaccharides31
raffinose30
stachyose31
chitooligosaccharides40
Mannose oligosaccharides40
triphala22
licorice40
codonopsis30
cellulose04
cinnamon30
ginger22
oregano04
turmeric40
taurine01
calanus oil––
nicotinamide mononucleotide40
Omega-313
Yeast beta-glucan04
Bacillus subtilis13
Bifidobacterium longum BB53603
Methylobacterium longum––
Bacillus coagulans13
Lactobacillus rhamnosus HN00104
Lactobacillus rhamnosus GG04
Lactobacillus rhamnosus CNCM I-3690––

Remember that the suggestions are based on the bacteria selected to be modified. Different selections produces different results.

The first one with major disagreement was Arabinogalactan. I extracted the citations that I used with the bacteria impacted and attach it below.

ArabinogalactanDownload

My Impression are:

  • For Supplements etc, we have 64% with reasonable agreement and 56% with strong agreement.
  • For Probiotics, we have zero agreement. 🙁
  • Items to AVOID are there — but the number is sparse, less than ideal.
    • The use of colors only is a poor UI choice (IMHO) because many people are color blind (8% of all males)
    • There is no words indicating this should be an avoid.

Bottom Line

Biomesight gives reasonable suggestions. The differences could be ascribed to the selection of bacteria needing modification. Microbiome Prescript default is to use 4 different algorithms to select bacteria and then aggregate into a consensus. I suspect Biomesight uses a single algorithm.

The absence of items to avoid is a significant omission IMHO.

I am a little concern for probiotic suggestions. This suggests two obvious possibilities: data entry issues or not sufficient coverage of available literature.

I would give their suggestions with supporting evidence a good rating. I suspect with enough time and manpower that they could raise it to excellent.

The videos below shows how you can see the evidence for the suggestions on Microbiome Prescription.

Ombre Suggestions Analysis – Failing Grade

This is part 2A of Comparing Microbiomes from Three Different Providers – Part 1. I decided to do each lab separately and then do an overview at the end.

Process

It is very simple, look at their suggestions, look at any references they provided. Then look at Microbiome Prescription evidence trail for the same substances. My usual “Just the facts, ma’am” approach. This data was retrieved on 24 Aug 2023.

They recommended their own brand mixture

Then we asked for suggests with no diet and no allergies.

At this point, I deem their evidence is grossly insufficient. Not one solid piece of evidence in almost 30 “scientific evidence”. I will say myself frustration (and the reader boredome) .

Using Microbiome Prescription Evidence

Most of the studies cited above were references to FODMAP, either low or high with this being ignored.

  • Multivariate modelling of faecal bacterial profiles of patients with IBS predicts responsiveness to a diet low in FODMAPs. Gut (Gut ) Vol: 67 Issue 5 Pages: 872-881 Pub: 2018 May Epub: 2017 Apr 17 Authors Bennet SMP , Böhn L , Störsrud S , Liljebo T , Collin L , Lindfors P , Törnblom H , Öhman L , Simrén M ,

For Tagliatelle (Pasta), we find the following study with adverse effect on many bacteria (it was an avoid)

  • Carbohydrate Staple Food Modulates Gut Microbiota of Mongolians in China. Frontiers in microbiology (Front Microbiol ) Vol: 8 Issue Pages: 484, Pub: 2017 Epub: 2017 Mar 21 Authors Li J , Hou Q , Zhang J , Xu H , Sun Z , Menghe B , Zhang H ,

Yuzu (Yuzu is a citrus fruit). This is not in the database, but another citric food is there, and it is a take suggestion

  • Analysis of Temporal Changes in Growth and Gene Expression for Commensal Gut Microbes in Response to the Polyphenol Naringenin. Microbiology insights (Microbiol Insights ) Vol: 11 Issue Pages: 1178636118775100 Pub: 2018 Epub: 2018 May 30 Authors Firrman J , Liu L , Argoty GA , Zhang L , Tomasula P , Wang M , Pontious S , Kobori M , Xiao W 
  •  The inhibitory effect of polyphenols on human gut microbiota. Journal of physiology and pharmacology : an official journal of the Polish Physiological Society (J Physiol Pharmacol ) Vol: 63 Issue 5 Pages: 497-503 Pub: 2012 Oct Epub: Authors Duda-Chodak A ,

For beans — we have the same citation to bean and soy tempeh 

For Garlic, we have it as an avoid with the following studies being the basis

  •  Effect of garlic powder on the growth of commensal bacteria from the gastrointestinal tract.
    Phytomedicine : international journal of phytotherapy and phytopharmacology (Phytomedicine ) Vol: 19 Issue 8-9 Pages: 707-11 Pub: 2012 Jun 15 Epub: 2012 Apr 4 Authors Filocamo A , Nueno-Palop C , Bisignano C , Mandalari G , Narbad A ,
  • Dietary prophage inducers and antimicrobials: toward landscaping the human gut microbiome.
    Gut microbes (Gut Microbes ) Vol: Issue Pages: 1-14 Pub: 2020 Jan 13 Epub: 2020 Jan 13 Authors Boling L , Cuevas DA , Grasis JA , Kang HS , Knowles B , Levi K , Maughan H , McNair K , Rojas MI , Sanchez SE , Smurthwaite C , Rohwer F
  • Inhibitory activity of garlic (Allium sativum) extract on multidrug-resistant Streptococcus mutans.
    Journal of the Indian Society of Pedodontics and Preventive Dentistry (J Indian Soc Pedod Prev Dent ) Vol: 25 Issue 4 Pages: 164-8 Pub: 2007 Oct-Dec Epub: Authors Fani MM , Kohanteb J , Dayaghi M 
  •  Effects of garlic polysaccharide on alcoholic liver fibrosis and intestinal microflora in mice.
    Pharmaceutical biology (Pharm Biol ) Vol: 56 Issue 1 Pages: 325-332 Pub: 2018 Dec Epub: Authors Wang Y , Guan M , Zhao X , Li X 
  • Black garlic melanoidins prevent obesity, reduce serum LPS levels and modulate the gut microbiota composition in high-fat diet-induced obese C57BL/6J mice. Food & function (Food Funct ) Vol: 11 Issue 11 Pages: 9585-9598 Pub: 2020 Nov 18 Epub: Authors Wu J , Liu Y , Dou Z , Wu T , Liu R , Sui W , Jin Y , Zhang M 

Their recommended probiotic contains the following species (with the evidence based suggestions count after):

  • L. Acidophilus – Mixed impact (2 plus, 1 minus)
  • E. Faecium – Avoid (3 minus)
  • L. Paracasei – MAJOR Avoid ( 4 minus)
  • L. Helveticus – Avoid ( 3 minus, 1 plus)
  • L. Rhamnosus – Mixed (2 plus, 2 minus)
  • L. Plantarum – MAJOR Avoid (4 minus)
  • B. Lactis – MAJOR Avoid (4 minus)
  • S. Boulardi – Mixed (2 plus, 2 minus)

IMHO, this is NOT a good mixture to take.

Bottom Line

Ombre’s suggestions for both probiotic and diet style leaves great opportunity to be made better. Their scientific citations is almost an embarrassment. I suspect that they were contracted out to a dietician and had no or poor quality control/review.

The videos below shows how you can see the evidence for the suggestions on Microbiome Prescription.

Comparing Microbiomes from Three Different Providers – Part 1

A reader did Ombre and Thorne from the same physical sample and then processed the Ombre results via Biomeisght resulting in three different reports on the same shit. That is:

  • Ombre (16s) – same digital data used
  • Biomesight (16s) – same digital data used
  • Thorne (MSS)

This is the first of two parts — the bacteria numbers as percentiles and percentages, The second part will look at suggestions from each (and provided documentation for why it was suggested when available).

As a reminder of issues, see the chart below and this earlier post: The taxonomy nightmare before Christmas… [2019]

From The gut microbiome and thromboembolism [2022]

From Standards seekers put the human microbiome in their sights, 2019

My intent is not to suggest/render judgements on the different test results, just show the differences. It should be noted that most studies are done with 16s and not MSS. Conclusions from one study may not be reproduceable using a different lab/software (even with the same digital data).

Pass #1: Percentile Rankings

These are the most likely to be similar between samples. I only looked at those bacteria reported by all three samples.

phylumThryveBiomeSightThorne
Acidobacteria761052
Actinobacteria384665
Bacteroidetes16679
Chloroflexi998888
Cyanobacteria969656
Firmicutes72866
Fusobacteria141078
Proteobacteria271429
Synergistetes46542
Tenericutes776137
Verrucomicrobia818364
classThryveBiomeSightThorne
Actinomycetia465462
Alphaproteobacteria355258
Anaerolineae338453
Bacilli846258
Bacteroidia16680
Betaproteobacteria241315
Caldilineae100791
Clostridia63907
Coriobacteriia768173
Cytophagia205877
Deltaproteobacteria817881
Epsilonproteobacteria687195
Erysipelotrichia182836
Fusobacteriia141078
Gammaproteobacteria473960
Mollicutes786135
Negativicutes90883
Opitutae597860
Synergistia46542
Tissierellia969988
Verrucomicrobiae818163
orderThryveBiomeSightThorne
Acholeplasmatales77624
Acidaminococcales202117
Actinomycetales939545
Alteromonadales169586
Anaerolineales332661
Bacillales904775
Bacteroidales16680
Bifidobacteriales302537
Burkholderiales241314
Caldilineales100791
Campylobacterales687196
Chromatiales459272
Coriobacteriales478411
Corynebacteriales919496
Cytophagales215877
Desulfovibrionales817880
Eggerthellales929496
Enterobacterales292267
Erysipelotrichales182836
Eubacteriales64897
Fusobacteriales141078
Halanaerobiales9410067
Hyphomicrobiales187494
Lactobacillales836761
Micrococcales39992
Micromonosporales741985
Mycoplasmatales878654
Nostocales729725
Oceanospirillales571089
Oscillatoriales958028
Puniceicoccales62161
Rhodospirillales85041
Rickettsiales291049
Selenomonadales858629
Streptosporangiales567876
Synergistales47542
Thermoanaerobacterales221848
Tissierellales959982
Veillonellales969210
Verrucomicrobiales818163
familyThryveBiomeSightThorne
Acholeplasmataceae77624
Acidaminococcaceae212117
Actinomycetaceae939566
Aerococcaceae929860
Akkermansiaceae828569
Anaerolineaceae352661
Atopobiaceae901671
Bacillaceae769897
Bacteroidaceae231555
Bifidobacteriaceae322541
Bradyrhizobiaceae342581
Caldilineaceae100791
Campylobacteraceae686695
Carnobacteriaceae521067
Clostridiaceae879412
Coprobacillaceae Verbarg et al. 201476421
Coriobacteriaceae18847
Corynebacteriaceae909295
Desulfovibrionaceae837880
Dysgonomonadaceae60479
Eggerthellaceae929496
Enterobacteriaceae582367
Enterococcaceae606289
Erysipelotrichaceae192539
Eubacteriaceae927729
Eubacteriales Family XIII. Incertae Sedis959666
Lachnospiraceae809326
Lactobacillaceae897464
Micrococcaceae161391
Microcoleaceae91771
Micromonosporaceae742085
Mycoplasmataceae878654
Odoribacteraceae979477
Oscillospiraceae345417
Paenibacillaceae954796
Peptococcaceae989039
Peptoniphilaceae959982
Peptostreptococcaceae478483
Planococcaceae308078
Porphyromonadaceae552736
Prevotellaceae585250
Puniceicoccaceae63581
Rhodospirillaceae104835
Rickettsiaceae351338
Selenomonadaceae818726
Sporomusaceae863846
Streptococcaceae556673
Streptosporangiaceae682052
Sutterellaceae24149
Syntrophomonadaceae96586
Tannerellaceae292076
Thermoactinomycetaceae858843
Turicibacteraceae Verbarg et al. 2014262722
Veillonellaceae969210
genusThryveBiomeSightThorne
Acetivibrio668614
Acetobacterium988513
Acholeplasma77486
Actinobaculum38833
Actinomyces747953
Actinotignum517162
Akkermansia828569
Alloscardovia93931
Anaerococcus949681
Anaerostipes907341
Arcanobacterium97975
Bacillus219396
Bacteroides261671
Bifidobacterium191844
Bilophila59612
Blautia84944
Brevibacillus418587
Butyricimonas735682
Butyrivibrio948774
Caloramator65607
Campylobacter676796
Clostridium788716
Coprobacillus87491
Coprococcus27422
Corynebacterium909295
Desulfotomaculum827560
Desulfovibrio698487
Dialister979345
Dorea90691
Dysgonomonas60440
Eggerthella757886
Enterococcus266788
Erysipelothrix766717
Escherichia723252
Ethanoligenens993747
Eubacterium925438
Faecalibacterium333221
Filifactor789750
Finegoldia908475
Gemella659718
Hathewaya88771
Helcococcus99876
Lachnospira59388
Lactobacillus896064
Ligilactobacillus581581
Limosilactobacillus242349
Mediterraneibacter868146
Megasphaera919741
Mobiluncus18163
Mogibacterium989631
Mycoplasma888647
Mycoplasmopsis35940
Negativicoccus759224
Odoribacter989858
Paenibacillus959996
Parabacteroides292076
Pectinatus23192
Peptococcus82901
Peptoniphilus959969
Phocaeicola32555
Porphyromonas949597
Prevotella676458
Pseudobutyrivibrio404328
Roseburia696063
Ruminiclostridium76465
Ruminococcus91848
Schaalia361026
Slackia378110
Streptococcus567075
Sutterella461416
Syntrophomonas97202
Thermoclostridium603834
Turicibacter262722
Varibaculum86862
Veillonella608420
Weissella871331

Pass #2: Percentage

phylumThryveBiomeSightThorne
Acidobacteria0.0110.0020.005
Actinobacteria0.6520.3642.117
Bacteroidetes12.52612.63360.723
Chloroflexi0.1830.020.02
Cyanobacteria0.1230.3740.024
Firmicutes82.6182.71727.458
Fusobacteria0.0020.0020.02
Proteobacteria1.1631.5021.894
Synergistetes0.0040.0020.005
Tenericutes0.0490.0480.015
Verrucomicrobia1.9941.9540.627
classThryveBiomeSightThorne
Actinomycetia0.6410.3511.093
Alphaproteobacteria0.0130.0850.171
Anaerolineae0.0020.0110.003
Bacilli2.9310.7290.765
Bacteroidia12.52210.23860.036
Betaproteobacteria0.2660.2630.175
Caldilineae0.1820.0090.001
Clostridia73.50881.68925.405
Coriobacteriia0.6650.5270.989
Cytophagia0.0040.0360.047
Deltaproteobacteria0.7230.7350.875
Epsilonproteobacteria0.0110.0090.275
Erysipelotrichia0.2810.1910.336
Fusobacteriia0.0020.0020.02
Gammaproteobacteria0.1520.1980.359
Mollicutes0.0490.0480.013
Negativicutes3.8393.40.069
Opitutae0.0040.0080.004
Synergistia0.0040.0020.005
Tissierellia1.4683.3520.386
Verrucomicrobiae1.9931.9460.621
orderThryveBiomeSightThorne
Acholeplasmatales0.0230.0330.002
Acidaminococcales0.0080.0070.007
Actinomycetales0.0920.3210.021
Alteromonadales0.0020.0650.021
Anaerolineales0.0020.0020.003
Bacillales0.2310.1470.233
Bacteroidales12.56710.23860.01
Bifidobacteriales0.1640.030.123
Burkholderiales0.2670.2590.127
Caldilineales0.1820.0090.001
Campylobacterales0.0110.0090.273
Chromatiales0.0040.030.013
Coriobacteriales0.1430.5270.025
Corynebacteriales0.1960.2020.81
Cytophagales0.0040.0360.047
Desulfovibrionales0.7160.7270.825
Eggerthellales0.5170.5250.963
Enterobacterales0.0110.0120.157
Erysipelotrichales0.2820.1910.336
Eubacteriales73.71780.55425.38
Fusobacteriales0.0020.0020.02
Halanaerobiales0.0130.2390.004
Hyphomicrobiales0.0020.0080.07
Lactobacillales2.710.3880.525
Micrococcales0.0060.0020.063
Micromonosporales0.0040.0020.006
Mycoplasmatales0.0210.0150.007
Nostocales0.0060.3570.005
Oceanospirillales0.0080.0020.02
Oscillatoriales0.1170.0090.002
Puniceicoccales0.0040.0020
Rhodospirillales0.0020.0690.021
Rickettsiales0.0020.0020.004
Selenomonadales0.0960.3920.02
Streptosporangiales0.0040.0080.007
Synergistales0.0040.0020.005
Thermoanaerobacterales0.0020.0070.019
Tissierellales0.993.4240.267
Veillonellales3.7493.40.041
Verrucomicrobiales21.9460.621
familyThryveBiomeSightThorne
Acholeplasmataceae0.0230.0330.002
Acidaminococcaceae0.0080.0070.007
Actinomycetaceae0.0960.0860.021
Aerococcaceae0.0960.0840.007
Akkermansiaceae2.071.9030.616
Anaerolineaceae0.0020.0020.003
Atopobiaceae0.1410.0020.018
Bacillaceae0.0140.070.085
Bacteroidaceae8.2067.86930.336
Bifidobacteriaceae0.170.030.123
Bradyrhizobiaceae0.0020.0020.011
Caldilineaceae0.1890.0090.001
Campylobacteraceae0.0120.0090.267
Carnobacteriaceae0.0040.0020.007
Clostridiaceae2.45611.8270.304
Coprobacillaceae Verbarg et al. 20140.0510.1380
Coriobacteriaceae0.0060.5270.007
Corynebacteriaceae0.1950.1920.776
Desulfovibrionaceae0.7430.7210.822
Dysgonomonadaceae0.0060.0020.023
Eggerthellaceae0.5370.5250.963
Enterobacteriaceae0.0120.0120.117
Enterococcaceae0.0040.0150.06
Erysipelotrichaceae0.2930.1380.336
Eubacteriaceae8.6370.250.054
Eubacteriales Family XIII. Incertae Sedis0.3770.1880.047
Lachnospiraceae35.55838.81715.522
Lactobacillaceae2.4880.0470.09
Micrococcaceae0.0020.0020.027
Microcoleaceae0.1210.0070.001
Micromonosporaceae0.0040.0020.006
Mycoplasmataceae0.0220.0150.006
Odoribacteraceae1.0280.9550.588
Oscillospiraceae1.60421.9735.153
Paenibacillaceae0.1050.0070.085
Peptococcaceae0.2950.1780.03
Peptoniphilaceae1.0283.4130.261
Peptostreptococcaceae0.1620.0470.81
Planococcaceae0.0060.0060.015
Porphyromonadaceae1.7010.8861.001
Prevotellaceae0.6540.5070.285
Puniceicoccaceae0.0040.0040
Rhodospirillaceae0.0020.0650.012
Rickettsiaceae0.0020.0020.002
Selenomonadaceae0.0780.3880.016
Sporomusaceae0.0220.0040.004
Streptococcaceae0.180.1650.344
Streptosporangiaceae0.0040.0020.003
Sutterellaceae0.2770.2550.028
Syntrophomonadaceae0.0160.0340.001
Tannerellaceae0.3890.5452.972
Thermoactinomycetaceae0.010.0150.004
Turicibacteraceae Verbarg et al. 20140.0040.0040.004
Veillonellaceae3.8923.40.041
genusThryveBiomeSightThorne
Acetivibrio0.0190.4730.007
Acetobacterium0.0150.1960.003
Acholeplasma0.0230.0070.001
Actinobaculum0.0020.0060
Actinomyces0.0150.0140.009
Actinotignum0.0040.0040.005
Akkermansia1.9951.9030.616
Alloscardovia0.0090.0090
Anaerococcus0.4140.4070.073
Anaerostipes4.8390.1440.173
Arcanobacterium0.030.030.001
Bacillus0.0020.0190.052
Bacteroides7.9087.86930.336
Bifidobacterium0.0170.0190.121
Bilophila0.2950.2920.002
Blautia13.00418.7271.315
Brevibacillus0.0020.0040.004
Butyricimonas0.1470.1420.374
Butyrivibrio0.2760.1080.066
Caloramator0.0230.2410.003
Campylobacter0.0110.0090.263
Clostridium1.0063.2040.188
Coprobacillus0.0510.1380
Coprococcus0.1960.0350.277
Corynebacterium0.1880.1920.761
Desulfotomaculum0.0170.0070.006
Desulfovibrio0.4140.4290.813
Dialister2.4482.0750.019
Dorea1.940.5350.001
Dysgonomonas0.0060.0020.006
Eggerthella0.0770.0460.139
Enterococcus0.0020.0130.056
Erysipelothrix0.0080.0190.003
Escherichia0.0110.010.03
Ethanoligenens0.7560.0040.007
Eubacterium8.2140.0390.051
Faecalibacterium6.4948.2614.065
Filifactor0.0080.0430.004
Finegoldia0.1540.0540.041
Gemella0.0060.0990.003
Hathewaya0.0130.3490.001
Helcococcus0.0240.0060.001
Lachnospira0.0047.1224.473
Lactobacillus2.3970.0170.043
Ligilactobacillus0.0060.0020.029
Limosilactobacillus0.0020.0020.003
Mediterraneibacter5.6610.8130.456
Megasphaera0.0360.1960.009
Mobiluncus0.0020.0020.001
Mogibacterium0.1430.1880.007
Mycoplasma0.0210.0150.006
Mycoplasmopsis0.0020.0150
Negativicoccus0.0080.060.002
Odoribacter0.8440.8130.202
Paenibacillus0.0980.0170.072
Parabacteroides0.3890.5452.955
Pectinatus0.0020.0040.001
Peptococcus0.0190.1450.001
Peptoniphilus0.3952.9460.09
Phocaeicola0.0023.92210.611
Porphyromonas0.3520.3351.001
Prevotella0.630.5070.158
Pseudobutyrivibrio0.0040.0760.022
Roseburia2.6752.713.37
Ruminiclostridium1.9950.0080.002
Ruminococcus8.9729.7360.374
Schaalia0.0040.0020.003
Slackia0.0080.1070.003
Streptococcus0.1710.1650.34
Sutterella0.2110.2550.028
Syntrophomonas0.0150.0020
Thermoclostridium0.0040.0060.004
Turicibacter0.0040.0040.004
Varibaculum0.0360.0340.001
Veillonella0.0230.5560.01
Weissella0.0170.0020.003

Bottom Line….

For some bacteria we have the numbers being close, and for others very, very different. Often we see percentage being 10x different between tests! For Percentile, we see one test reforming 91%ile and a different test reporting 1%.

A human analogy: You pick a person off the street and ask “What is this person?” A Canadian? A Swede?

There is usually no clear answer —

  • Their name may indicate Iceland — Guðrún Jónsdóttir
  • Their passport may indicate that they are a Canadian Citizen
  • Their skin color may indicate that they are from Africa
  • Their nose may suggest that are from the Mediterranean
  • Their DNA may suggest that they are part Nigerian, Finnish, Thai, Irish
    • They are mitochondrial Haplogroup K, very common among Jewish People
  • Their eating habits suggests they may be Hindu
  • The way they speak English suggests that they are Haida Gwaii (native tribe on Canada’s west coast)
  • Their music preference (opera) suggests Italian

Bacteria exchange RNA etc constantly — just like our humans! We may want to have definitive answers — we should fix ourselves before complaining about bacteria! ;-). Different tests use different characteristics to give a bacteria a name.

What I am curious about is whether these changes make dramatic changes in suggestions.

Exploration: Salicylate Sensitivity And the Microbiome

These are notes in progress. Use them at your own risk

In terms of KEGG data, one enzyme stands out: ATP:L-threonine O3-phosphotransferase (2.7.1.177). This is referred to as L-threonine in simpler terms. The people with this sensitivity has 10% of the levels of people not reporting it and there is a value for almost every sample.

This lead to this interest quote (dealing with plants)

  • “Salicylic acid[SA] .. in the rhizosphere may be strongly reduced, or completely abolished, due to the presence of histidine and threonine in the root exudates.” [2014] in other threonine may be a key chemical is processing SA.

Checking for the bacteria known to produce the EC2.7.1.177 ATP:L-threonine O3-phosphotransferase the top 3 are:

  • Clostridium difficile [species] at 639
  • Veillonella dispar [species] at 554
  • Megamonas funiformis [species] at 534
  • Megasphaera elsdenii [species] at 392

There are no probiotics that produces it. It is available as a supplement, with WebMd suggests this dosage of “Early research suggests that taking 1.5 grams to 2 grams of threonine by mouth three times daily might improve some symptoms in people with familial spastic paraparesis. But the improvement does not seem to be very significant.”

I was unable to find anyone trying this for Salicylate Sensitivity (Hint: any volunteers?)

Salicylate Issues

I did an analysis looking at the frequency percentage of a bacteria being found for Biomesight samples (the largest collection). The key items are below. The higher the Chi2 value, the more likely it is.

Tax_NameTax_RankWithConditionNoConditionChi2
Oceanospirillaceaefamily51.7 (Over)24.98.18
Ruminococcus callidusspecies24.1 (Under)56.35.3
Macrococcus
(in Staphylococcaceae family)		genus58.6 (Over)35.74.16
Amedibacillusgenus96.6 (Over)66.73.81
Biomesight Data

There was not sufficient data on Ombre samples

The substances that reduces these overgrowths are: Cacao, green tea, kefir, lychee fruit,  papaya, rhubarb, rosehip tea,  trametes versicolor(Turkey tail mushroom), Slippery Elm. Many of these are low in salicylate (check each one before doing).

Histamine Issues

I did an analysis looking at the frequency percentage of a bacteria being found for Biomesight samples (the largest collection). The statistically significant items are below, with 1 overgrowth “Streptococcus oralis” and the rest as undergrowth . The higher the Chi2 value, the more likely it is.

Tax_NameTax_RankWithConditionNoConditionChi2
Clostridium chartatabidumspecies16.529.46.54
Euryarchaeotaphylum14.926.96.29
Methanobacteriaceaefamily14.926.35.75
Streptococcus oralis subsp. tigurinussubspecies57.943.75.13
Heliobacteriaceaefamily30.644.14.8
Ruminococcus callidusspecies42.156.74.31
Bifidobacterium asteroidesspecies20.731.44.29
Thermosediminibacteralesorder27.338.53.82
From Biomesight Samples
Tax_NameTax_RankWithConditionNoConditionChi2
Actinopolysporalesorder38.824.18.83
Anaeroplasmataceaefamily50.934.47.77
Desulfocellagenus43.128.67.26
Desulfocella halophilaspecies42.228.36.8
Rhodocyclalesorder45.731.86
Burkholderiaceaefamily42.229.35.77
Spirosomaceaefamily74.156.85.35
Rothia mucilaginosaspecies1931.45.33
Ruminococcus gauvreauiispecies47.4345.28
Rhodocyclaceaefamily4431.25.19
Ezakiellagenus39.7284.85
Holdemania massiliensisspecies4431.74.71
Limosilactobacillusgenus38.827.64.62
Cytophagaceaefamily85.368.14.47
Bacteroides fluxusspecies6953.64.45
Halobacteroidaceaefamily44.832.94.44
Oscillibacter valericigenesspecies44.832.94.37
Senegalimassiliagenus44.832.94.35
Flammeovirgaceaefamily42.231.14.03
Hungateiclostridiumgenus56.943.83.95
From Ombre Data