Author: Research

Psychoactive Probiotics! – 2024 Update for Dopamine

A reader asked me to do an update of my 2016 post Psychoactive Probiotics! There has been a lot of recent literature as shown on PubMed. Note that often these are strain specific and not generalized for species cited below. If you cannot find the strains specified in the studies, it may be worthwhile trying different brands of the species (with the most studied species being most probable).

Excessive Dopamine may be associated with: Mania or Hypomania, Psychosis, Substance Use Disorders, Hyperactivity and Impulsivity, Tics and Tourette Syndrome, Sleep Disorders, Huntington’s Disease and Excessive Reward Seeking Behavior. Insufficient dopamine may be associated with: Parkinson’s Disease, Depression, Attention-Deficit/Hyperactivity Disorder (ADHD), Drug Addiction and Substance Use Disorders, Restless Legs Syndrome, Schizophrenia and Huntington’s Disease.

Catalog

Warnimgs:

The following appears to reduce dopamine

Lacticaseibacillus casei LA205 and Lacticaseibacillus paracasei LA903 REDUCES Dopamine [2023]

Lactobacillus delbrueckii  [2021]

Lactobacillus plantarum DR7 [2019] but increases serotonin 

Bifidobacterium CECT 7765 [2017]

Psychoactive Probiotics! – 2024 Update for GABA

A reader asked me to do an update of my 2016 post Psychoactive Probiotics! There has been a lot of recent literature as shown on PubMed. Note that often these are strain specific and not generalized for species cited below. If you cannot find the strains specified in the studies, it may be worthwhile trying different brands of the species (with the most studied species being most probable).

Excessive GABA may be associated with Huntington’s disease, epilepsy, and certain types of encephalopathies. Insufficient GABA may be associated with Anxiety Disorders, Epilepsy, Sleep Disorders, Mood Disorders, Substance Use Disorders, Movement Disorders, Neuropathic Pain and Autism Spectrum Disorders.

“Metagenomic analyses suggest that the genomes of many gut bacteria encode glutamate decarboxylase (GAD), the enzyme that catalyzes GABA production.” [2023]

“Stress exposure induced a decline in Lactobacillaceae abundance and hence γ-aminobutyric acid (GABA) level in mice.” [2023]

Note: monosodium glutamate (MSG) can increase the production of GABA [2024]

Effect of Probiotic Therapy on Neuropsychiatric Manifestations in Children with Multiple Neurotransmitter Disorders: A Study[2023] “The results indicate that psychobiotics have a significant impact on reducing hyperactivity and aggression, and improving concentration“

Probiotic Catalog

NOTE: The current official name is used below. Most L. species were known as Lactobacillus with older names.

Note: Gamma aminobutyric acid production by commercially available probiotic strains [2023] cites that the best are: Levilactobacillus brevis LB01 [Source], Lactiplantibacillus plantarum 299v [Jarrow Formulas Ideal Bowel Support].

Lactiplantibacillus plantarum 299v is the most available with many suppliers. A dosage of 10-60 BCFU per day is recommended.

Allergies, Asthma, CFS – then a semi-miracle.

Backstory

I think I grew up with dysbiosis, as evidenced by allergies, mild asthma, and neuro divergencies (extremely withdrawn and attention deficit). In my 20s developed mild semi-functional CFS due to chronic stress.

In 2020 was exposed to black mold, and had a short very strange illness around this time. Then later I got the first 2 covid vaccines, followed by the booster Dec 2021, which was my major trigger.
Symptoms: Shortness of breath, CFS, chest pain,chest pressure, palpitation, insomnia, fight or flight/anxiety, hallucinations, joint pain, food intolerance, histamine issues, exercise intolerance, PEM, tinnitis, nausea, apparent veinous insufficiency, endotheliatis head pressure, neck pain, POTS, etc. I also grew a nerve tumor (this appeared 2 years later). EBV antibodies showed very high.

Some of these symptoms have gone away, and my intensity of illness is maybe 1/3 of what it was in the beginning, but I seem to have reached a plateau. My Biomesight showed a bunch of issues and I’m looking to correct it in order to give my immune system a chance to normalize.

Analysis

We see an excessive number of bacteria/taxa at very high levels, suggesting they are dominating the microbiome.

Drilling down to Health Indicators

With Dr. Jason Hawrelak Recommendations, we are at the 66%ile, a reasonable level.  The MHI-A ratio is low, indicating issues. With Bacteria deemed Unhealthy, Streptococcus vestibularis(An unhealthy Predictor) was at 98%ile and Escherichia coli was at 96%ile. E.Coli can be good or bad (16s is not able to tell them apart) — an ad-hoc test is to try Mutaflor probiotics (E-Coli Nissle 1917) and if there is either a major herx or major improvement, then we can assume a major bad E.Coli component. Mutaflor is aggressive against bad E. Coli.

Using Potential Medical Conditions Detected, one items is a strong match: Postural orthostatic tachycardia syndrome at 85%ile

Using the new Taxa-Symptom Association, we find some strong matches at the order level, which are not there at the genus level. The highest possible factor is 100 (matching every association).

For information on this feature see: Evolution of Addressing Microbiome/Gut issues which includes a video.

Looking at Black Mold, Prevotella growth is associated with mold. We are relatively high, 81%ile. Associations of observed home dampness and mold with the fungal and bacterial
microbiomes [2021]. However, the mold in the environment predictor is at the 30%ile. General advice is to check (and test) for mold in home and work environment; keep humidity low in both.

Scanning General Health Predictors, the only item that stood out was low Vitamin K2 production, which suggests that Vitamin K supplements may be beneficial.

Going Forward

I am going to do [Just Give me suggestion with symptoms] and then suggestions using Order above (the taxa rank that has the highest factor (best match)]. This gives us 6 sets of suggestions. Taxa “Order” is above the data for antibiotics, so sorting to only those items with 6 Takes, we end up with a clean list shown below of all suggestions saying take with high Priorities — sweet!. Lactobacillus casei, siblings (paracasei) and lactobacillus casei shirota (probiotics) dominate probiotics to the exclusion of other probiotics. This group is well known to help allergies and reduce histamine issues.

Items to Take

Priority  ModifierModifier Type
554.7lactobacillus casei (probiotics)Probiotics
499.6CurcuminHerb or Spice
496.6vitamin B3,niacinVitamins, Minerals and similar
485.8garlic (allium sativum)Herb or Spice
479.1Hesperidin (polyphenol)flavonoids, polyphenols etc
469.2lactobacillus paracasei (probiotics)Probiotics
445.9Vitamin B1,thiamine hydrochlorideVitamins, Minerals and similar
443.1Arbutin (polyphenol)flavonoids, polyphenols etc
443.1diosmin,(polyphenol)flavonoids, polyphenols etc
443.1luteolin (flavonoid)flavonoids, polyphenols etc
443.1retinoic acid,(Vitamin A derivative)Vitamins, Minerals and similar
443.1Theobromine (in food)Prescription – Other
443.1Vitamin B6,pyridoxine hydrochlorideVitamins, Minerals and similar
407.2Vitamin B-12Vitamins, Minerals and similar
403tannic acidHerb or Spice
395soyFood (excluding seasonings)
385.1melatonin supplementAmino Acid and similar
327Guaiacol (polyphenol)flavonoids, polyphenols etc
324.2schinus molle (herb)Herb or Spice
302sesuvium portulacastrum herbHerb or Spice
300.5lactobacillus casei shirota (probiotics)Probiotics
298.3tabebuia impetiginosa (taheebo) barkHerb or Spice
283.7CaffeineFood (excluding seasonings)
278.9wheyFood (excluding seasonings)
277.4Human milk oligosaccharides (prebiotic, Holigos, Stachyose)Prebiotics and similar
271.9teaFood (excluding seasonings)
262.3low-fat dietsDiet Style
254.6lactoseSugar and similar
251.8vitamin B7, biotinVitamins, Minerals and similar
246.7chitosan,(sugar)Sugar and similar

Items to Avoid

At the other end, only a few items were on the to avoid for all 6 sets of suggestions.

Priority  ModifierModifier Type
-443.8oligosaccharides (prebiotic)Prebiotics and similar [6]
-411.1BofutsushosanHerb or Spice [6]
-403.4non-starch polysaccharidesSugar and similar [6]
-340.6Slippery ElmHerb or Spice
-335.8bacillus coagulans (probiotics)Probiotics [6]
-334.4arabinogalactan (prebiotic)Prebiotics and similar
-314.7lupin seeds (anaphylaxis risk, toxic if not prepared properly)Food (excluding seasonings)
-301.7carobFood (excluding seasonings)
-298.3levanSugar and similar
-289.2PulsesFood (excluding seasonings)
-276.2l-prolineAmino Acid and similar
-254.6macrolide ((antibiotic)s)Antibiotics, Antivirals etc
-252.8vegetariansFood (excluding seasonings) [6]
-252.5Bile Acid SequestrantMiscellaneous, food additives, and other odd items
-247.9dietary phytoestrogens (isoflavones)Diet Style
-245.6pectinFood (excluding seasonings)
-241.7barley,oatFood (excluding seasonings)
-241.7resistant maltodextrinPrebiotics and similar
-236.3amaranthFood (excluding seasonings)
-235.3fastingFood (excluding seasonings)
-232.6Dendrobium officinaleHerb or Spice
-226.2fruit/legume fibreFood (excluding seasonings)
-221.1Ferric citrateVitamins, Minerals and similar
-220.7xylan (prebiotic)Prebiotics and similar
-218.8disodium fumarate (food additive)Miscellaneous, food additives, and other odd items
-216.5dairyFood (excluding seasonings)
-216.3Olive OilDiet Style
-215.4vsl#3 (probiotics)Probiotics
-212.1high-fat sucroseFood (excluding seasonings)

Bottom Line

I was also a person who responded very well to Mutaflor (we always have some in the fridge). In my case, the initial response was massive herxing for two weeks.

General Guidance

For items to take, remember that goal is to disrupt the dysbiosis. This means subjecting it to constantly changing “shocks” so it is unable to adapt. This has been shown to be effective when dealing with antibiotics (i.e. rotating between different antibiotics with breaks is more effective than taking the same antibiotic continuously).

My suggestion for a rotating 4 week cycle changing probiotics and herbs every week. Be aware of not falling into either the homeopathic or product labelling traps — that is, taking less then therapeutic levels. To determine those dosages see Supplement Dosages. In general, you want to be close to the maximum dosages used in studies (i.e. “deemed safe dosages”).

Vitamins and polyphenols can be taken continuously.

Feedback

Honestly, whatever algorithm is being used for symptoms is nothing short of amazing 

POTS is probably my main challenge, and I have all but two of the other symptoms. And the two that I don’t currently have (joint pain and insomnia) I have had in the past. So basically it’s 100% accurate in my case

For interventions- A friend of mine just mentioned diosmin to me the other day. B3, B1, HMO, caffeine have all  been helpful. Amazed to see Curcumin so high as it’s not really something I considered trying. 

Mutaflor has been amazingly helpful the last few days (neurotransmitters and gut and fatigue) but I’ve heard it can’t be taken with other probiotics due to competing?

I’m interested in Lactulose for the bifido also, as I’ve heard a lot about this recently..  Thanks for taking the time, very very interesting!
Also, one question if you have a moment. Are the interventions supposed to – directly improve the biome Or improve symptoms?

From first draft sent to him.

Answer: The data is computed to correct the bacteria shifts with statistical associations to symptoms. Adding suggestions for symptoms is another massive data extraction and entering. Readers can do cross validation for symptoms if they are inclined to search the literature (https://pubmed.ncbi.nlm.nih.gov/ )

Here’s an example: https://blog.microbiomeprescription.com/2023/02/12/cross-validation-of-ai-suggestions-for-nonalcoholic-fatty-liver-disease/

Many suggestions have never been tried against the symptoms.

Q: Or can the herbs possibly be mixed w probiotics?

  • Yes they can, but you should check that the herb does not inhibit the probiotics currently being taken. To do this, just click on the herb, You want compatible probiotics with the herbs.

Q: Also, do your algorithms pick up probability of sleep apnea and cancer? These are conditions I’m trying to assess my risk of having / getting 

  • They do pattern matching by two methods:
    • Articles on the US National Library of Medicine (go to https://microbiomeprescription.com/Library/PubMed ) AFTER LOGGING IN. It gives the percentile ranking of the number of matches you have compare to other samples.
    • Citizen Science based on self-reported symptoms and diagnosis. At present only Sleep Apnea Diagnosis has sufficient data for biomesight samples. For Sleep Apnea, you have 63% of the shifts matching which suggests that you may be heading in that direction, but sleep disturbances have much higher matches.

Q: This is extremely helpful Do you have any idea if there would be an interaction between mutaflor and lactulose? Mutaflor has still been amazing , semi- miraculous. It’s working so well I haven’t tried anything else yet. But I am very keen to get my bifido up 

A: It’s an easy lookup on the site. https://microbiomeprescription.com/library/modifier?mid2=1709  and it links to 2 studies which reports it.


Postscript – and Reminder

I am not a licensed medical professional and there are strict laws where I live about “appearing to practice medicine”.  I am safe when it is “academic models” and I keep to the language of science, especially statistics. I am not safe when the explanations have possible overtones of advising a patient instead of presenting data to be evaluated by a medical professional before implementing.

I cannot tell people what they should take or not take. I can inform people items that have better odds of improving their microbiome as a results on numeric calculations. I am a trained experienced statistician with appropriate degrees and professional memberships. All suggestions should be reviewed by your medical professional before starting.

The answers above describe my logic and thinking and is not intended to give advice to this person or any one. Always review with your knowledgeable medical professional.Posted on  by Research and tagged 

Eubiosis Revisited

Recently I have gotten some messages concerned about Eubiosis scores dropping. Eubiosis is a measure of evenness of the bacteria representation. It cannot be used to identify which bacteria needs to be changed. It is a representation of the Chi2 value of the genus converted to %ile with values over 80%ile deemed 100%.

What is statistically ideal is:

Below is an example of a low score of 1.2%

Dr. Jason Hawrelak score is 28%ile, MHI-A Ratio is 47%

It is saying that you have very few bacteria genus that have high representations and a ton of bacteria with high representation. This patterns suggest that the gut has become destabilized (which if you have dysbiosis is a good thing) but has not stabilized.

Same Person – Prior Pattern

The person has improved compared to this pattern. The “peak: was at 10-19 and above it has shifted to 10-29 range. Dr. Jason Hawrelak score is 46%ile MHI-A Ratio 67%

Same Person — further back

This is a better looking pattern. But remember this is not a primary measure for a gut score, but an adjunct dimension to be considered. For example, Dr. Jason Hawrelak score is a low 5%ile. MHI-A Ratio 66%ile

Bottom Line

There is no single number that represents an accurate gut health score. DO NOT DEEM EUBIOSIS to be such. It should be considered with items like: Dr. Jason Hawrelak score at least, and MHI-A Ratio ( see Development and Validation of a Novel Microbiome-Based Biomarker of Post-antibiotic Dysbiosis and Subsequent Restoration). Microbiome Prescription gives a multitude of different numbers estimating gut health based on literature, or in this case, statistics.

Gender based Microbiome Shifts for ME/CFS and other conditions

A question was ask – are there significant gender differences with ME/CFS. A partial answer is possible from our citizen science data (Available here). The number of bacteria identify as statistical significant drops because we are reducing sample sizes. The table below shows the shifts that are seen in common with P < 0.01.

For Symptom of ME/CFS

SourceTax_nametax_rankMaleFemaleMale_Chi2FeMale_Chi2
thryveThermodesulfobacteriaphylumincreasesincreases234.0375138.4544
biomesightVerrucomicrobiaceaefamilyincreasesincreases8.3333337.262051
biomesightRhodothermaeotaphylumincreasesincreases179.2217.3071
biomesightAkkermansiaceaefamilyincreasesincreases8.7183789.965634
biomesightErysipelothrix murisspeciesincreasesincreases9.53388910.08333
biomesightAkkermansiagenusincreasesincreases8.7183789.965634
biomesightRhodothermalesorderincreasesincreases179.2217.3071
biomesightAkkermansia muciniphilaspeciesincreasesincreases8.7183789.965634
biomesightErysipelothrixgenusincreasesincreases9.6632899.663289
biomesightRhodothermiaclassincreasesincreases179.2217.3071
biomesightThermodesulfobacteriaphylumincreasesincreases281.1738299.9112

ME/CFS With IBS

We find differences here.

SourceTax_nametax_rankTaxonMaleFemaleMale_Chi2FeMale_Chi2
biomesightSutterellagenus40544decreaseincreases8.33333311.25018
biomesightRhodothermalesorder1853224increasesincreases139.9274114.5716
biomesightDoreagenus189330increasesdecrease18.7516.17875
biomesightRhodothermiaclass1853222increasesincreases139.9274114.5716
biomesightThermodesulfobacteriaphylum200940increasesincreases280.3333187.9779
biomesightSutterellaceaefamily995019decreaseincreases8.33333311.25018
biomesightAlcaligenaceaefamily506decreaseincreases8.3333339.120714
biomesightRhodothermaeotaphylum1853220increasesincreases139.9274114.5716

ME/CFS Without IBS

We found no differences yet (given the sample size)

SourceTax_nametax_rankTaxonMaleFemaleMale_Chi2FeMale_Chi2
biomesightBacteroides fluxusspecies626930increasesincreases7.3551617.910588
biomesightThermodesulfobacteriaphylum200940increasesincreases124.4571170.4624

Irritable Bowel Syndrome

Following up from above and noting that there is a gender bias in incidence, we find some differences

thryveThermodesulfobacteriaphylum200940increasesincreases252.823295.10095
biomesightRhodothermalesorder1853224increasesincreases125.1467110.6182
biomesightRhodothermiaclass1853222increasesincreases125.1467110.6182
biomesightThermodesulfobacteriaphylum200940increasesincreases314.4971174.6182
biomesightRhodothermaeotaphylum1853220increasesincreases125.1467110.6182
biomesightSharpea azabuensisspecies322505increasesincreases16.185266.80625
biomesightSharpeagenus519427increasesincreases16.185266.80625
thryveMycoplasmagenus2093increasesdecrease12.8152420.3229
thryveMycoplasmataceaefamily2092increasesdecrease14.8858120.3229
thryvePhocaeicola vulgatusspecies821increasesdecrease7.89349217.06273
thryveMycoplasmatalesorder2085increasesdecrease14.8858126.01485

Depression

Another condition with a gender association

SourceTax_nametax_rankTaxonMaleFemaleMale_Chi2FeMale_Chi2
thryveThermodesulfobacteriaphylum200940increasesincreases227.7557148.4336
thryveParabacteroides distasonisspecies823decreaseincreases9.11835613.46941
thryveEubacterium oxidoreducensspecies1732decreaseincreases12.995076.76
biomesightRhodothermalesorder1853224increasesincreases121.200291.125
biomesightRhodothermiaclass1853222increasesincreases121.200291.125
biomesightThermodesulfobacteriaphylum200940increasesincreases223.4402189.2431
biomesightRhodothermaeotaphylum1853220increasesincreases121.200291.125
thryveLactobacillus rogosaespecies706562decreasedecrease23.8836812.12781

Symptom: Problems remembering things

This is one of the characteristics of ME/CFS, Long Covid, etc

SourceTax_nametax_rankTaxonMaleFemaleMale_Chi2FeMale_Chi2
thryveThermodesulfobacteriaphylum200940increasesincreases316.4446120.0944
biomesightRhodothermalesorder1853224increasesincreases171.7445133.3333
biomesightRhodothermiaclass1853222increasesincreases171.7445133.3333
biomesightThermodesulfobacteriaphylum200940increasesincreases369.0078289.0992
biomesightOdoribacteraceaefamily1853231increasesincreases12.793117.962632
biomesightRhodothermaeotaphylum1853220increasesincreases171.7445133.3333
biomesightAcetivibriogenus35829decreaseincreases9.18086517.49208
biomesightOdoribactergenus283168increasesincreases9.33494912
biomesightAcetivibrio alkalicellulosispecies320502decreaseincreases9.18086519.95636
biomesightHathewaya histolyticaspecies1498decreaseincreases9.1808657.262051
biomesightHathewayagenus1769729decreaseincreases9.1808657.262051
biomesight[Clostridium] thermoalcaliphilumspecies29349increasesincreases7.356.880909
thryveIntestinimonasgenus1392389decreaseincreases168.552727
thryveIntestinimonas butyriciproducensspecies1297617decreaseincreases16.486469.992258
ubiomeBacteroides sp. EBA5-17species447029increasesdecrease9.0555777.314286

Symptom: Worsening of symptoms with stress.

Another common symptom of ME/CFS

SourceTax_nametax_rankTaxonMaleFemaleMale_Chi2FeMale_Chi2
thryveThermodesulfobacteriaphylum200940increasesincreases282.4023185.22
biomesightThermoanaerobacterales Family III. Incertae Sedisfamily543371decreaseincreases22.004548.491649
biomesightSharpeagenus519427increasesincreases17.5562512.38345
biomesightHathewayagenus1769729decreaseincreases16.9861211.70814
biomesightRhodothermalesorder1853224increasesincreases142.9353188.8704
biomesightHathewaya histolyticaspecies1498decreaseincreases16.9861211.70814
biomesightSharpea azabuensisspecies322505increasesincreases17.5562512.97965
biomesightRhodothermiaclass1853222increasesincreases142.9353188.8704
biomesightThermodesulfobacteriaphylum200940increasesincreases352.2616362.7038
biomesightAcetivibrio alkalicellulosispecies320502decreaseincreases12.658188.491649
biomesightRhodothermaeotaphylum1853220increasesincreases142.9353188.8704
biomesightAcetivibriogenus35829decreaseincreases12.658188.491649

Other Symptoms with Significant Gender Differences in patterns

  • Immune Manifestations: Abdominal Pain
  • Sleep: Unrefreshed sleep
  • Comorbid: High Anxiety
  • General: Fatigue
  • Neurological-Audio: hypersensitivity to noise
  • DePaul University Fatigue Questionnaire : Unrefreshing Sleep, that is waking up feeling tired
  • DePaul University Fatigue Questionnaire : Fatigue
  • Neurocognitive: Brain Fog
  • Neurocognitive: Problems remembering things
  • DePaul University Fatigue Questionnaire : Anxiety/tension
  • General: Myalgia (pain)
  • Immune Manifestations: Constipation
  • Post-exertional malaise: Rapid muscular fatigability,
  • Neuroendocrine Manifestations: Poor gut motility
  • Comorbid: Restless Leg
  • Comorbid: Small intestinal bacterial overgrowth (SIBO)
  • DePaul University Fatigue Questionnaire : Difficulty finding the right word
  • DePaul University Fatigue Questionnaire : Mood swings
  • DePaul University Fatigue Questionnaire : Pain in Multiple Joints without Swelling or Redness
  • Sleep: Problems falling asleep
  • Sleep: Problems staying asleep

New Clues Into Mystery of Itch – Exploration

A reader pointed me at S. aureus drives itch and scratch-induced skin damage through a V8 protease-PAR1 axis [2021]. There is a prescription drug, PAR-1 INHIBITORS, that appears to help (with some risks).

It is not all strains of Staphylococcus aureus, but about 10% of the strains.

Normally, I look at modifying the gut microbiome — but many items are likely to help. So the question becomes, what are possible for use as skin ointments?

From the list of inhibitors, likely candidates are:

  • Zinc or silver ointments
  • acetic acid (vinegar) – likely diluted, possibly with a sprayer
  • The following available as oils, mixed with creams:
    • oregano oil (2nd high studies)
    • thyme oil (MOST STUDIES)
    • lauric oil / coconut oil
    • clove oil
    • cinnamon oil
    • peppermint oil
    • coriander oil
  • Other items that may be semi liquid:
  • Following in solution
    • aspartame (sweetener)
    • saccharin
    • stevia
    • sucralose

The following should NOT be applied to the skin:

  • Olive oil

User Feedback

A person with this issue looked over the list and found that the items in the above list that she has tried, reduced the itch.

The obvious cheapest solution to try is simple: a shower with soap (ideally antibacterial soap). Followed by using a spray bottle with vinegar that is allowed to dry on the skin.

Other items that inhibits: [2012]

  • paroxetine
  • hydroxyzine
  • atomoxetine
  • bencyclane fumarate

Jason Hawrelak Criteria for Healthy Gut – Revisited

This is an update Jason Hawrelak Criteria for Healthy Gut. His criteria is based on percentages and used by medical practitioners around the world. I have three significant collections of samples and decided to find out how these percentages translate to percentile for each lab.

They are similar and not similar. For example 50% of people will have low Akkermansia using uBiome while Biomesight increases it to 77%. Alistipes — are never out of range for Biomesight while 90% of people using uBiome would be too high.

Taxa NameTaxa RankPercentageuBiome PercentileOmbre PercentileBiomesight Percentile
Akkermansiagenus1 – 548 – 8071 – 9177 – 93
Alistipesgenus0 – 0.30 – 100 – 330 – 100
Bacteroidesgenus0 – 200 – 320 – 480 – 45
Bacteroidiaclass0 – 350 – 240 – 400 – 45
Bifidobacteriumgenus2.5 – 578 – 9178 – 8790 – 95
Bilophila wadsworthiaspecies0 – 0.150 – 320 – 430 – 44
Blautiagenus5 – 1015 – 6032 – 7224 – 69
Desulfovibriogenus0 – 0.150 – 460 – 420 – 72
Escherichia colispecies0 – 0.10 – 1000 – 750 – 88
Eubacteriumgenus0 – 150 – 1000 – 990 – 100
Faecalibacterium prausnitziispecies10 – 1580 – 9550 – 6946 – 69
Fusobacteriumgenus0 – 0.010 – 400 – 660 – 72
Lactobacillusgenus0.01 – 123 – 939 – 7546 – 99
Methanobrevibactergenus0 – 0.010 – 70 – 330 – 33
Oxalobactergenus0.01 – 10 – 10038 – 10035 – 100
Prevotellagenus0 – 250 – 1000 – 890 – 88
Pseudomonadotaphylum0 – 40 – 520 – 760 – 54
Roseburiagenus5 – 1051 – 8685 – 9681 – 95
Ruminococcusgenus0 – 150 – 1000 – 9810- 95

This post is intended to illustrate that percentages cannot be determined by one lab and applied to another. Percentile appears to be more robust.

Evolution of Addressing Microbiome/Gut issues

There are generations of approaches. Often limited to the knowledge available at the time

Generation #1: Eat Fermented Foods as a Cure All

This dates back millennium in the east and the west. It helps some, and thus is validated as working (for some at least). For example, Garum in ancient Greece

Generation #2: Yogurt and Probiotics

In western culture, The Russian biologist and Nobel laureate Ilya Mechnikov, from the Institut Pasteur in Paris, was influenced by Grigorov’s work and hypothesized that regular consumption of yogurt was responsible for the unusually long lifespans of Bulgarian peasants.[25] Believing Lactobacillus to be essential for good health, Mechnikov worked to popularize yogurt as a foodstuff throughout Europe. [Wikipedia]

Generation #3: Bacteria Shifts

This arose out of the new technologies to identify bacteria in better detail. This was in the 1950’s and later [Experience with antibiotics. II. Shifts in bacterial flora in man].

There are several generation of technology involved here.

“A significant difference in gut microbial composition between SARS-CoV-2 positive and negative samples was observed, with Klebsiella and Agathobacter being enriched in the positive cohort.”

The gut microbiome of COVID-19 recovered patients returns to uninfected status in a minority-dominated United States cohort [2021]

These studies indicates an increase or decrease in the average for populations. There is no thresholds where the odds change nor relative magnitude. This is further complicated by non-replication by other researchers — the reason is often because on non-standardization of microbiome analysis

Generation #4: Lab Specific Shifts with critical levels and contributions

Using large dataset and techniques such as those described in Symptoms with Ability to Predict from Microbiome Results. We have the ability to set threshold and determine the relative importance. The table below is for Long COVID based on one lab’s pipeline. We can easy see the pattern — often, it is a relatively rare bacteria(low prevalence) that is seen in significant levels in Long COVID patients

This allows identification of the genus (or other ranks) that may be ascribe to the condition if over the 84%ile. It also allows the relative importance of each to be evaluated since there may be multiple targeted bacteria. Chi2 value is a reasonable proxy for importance.

Moving up the taxonomical rank, we see at the ORDER level that one order is really significant.

Bottom Line

IMHO, this last method allows superior identification of bacteria involved with conditions and symptoms using two simple cutoff points: <= 16%ile and >=84%ile. Other cutoff points are possible,
We can then look at a patient’s microbiome (assuming suitable lab-pipeline) and identify with statistical accuracy which bacteria are involved. Not only can we identify the bacteria — we can determine the relative importance of each bacteria.

Strong Genus association to many conditions

This week I refactor the genus association algorithm resulting in clearer results. I also change it so the common person can understand what is being reported.

The core is that once we convert percentage to percentiles, we end up with a “flat” or uniform distribution. For any genus, we have the same number in 0-10%ile, 50-60%ile and 90-100%. If there is no association, we should see the same number in the 0-16%ile and 84-100%ile. If there are not, we can compute the statistical significance (I picked p < 0.01 or one chance in 100 of not being a true association).

Below, we will cover 2 pages and a FYI:

Extreme Associations

Processing without considering genus (i.e. all tax ranks) The following association occurs with extremely high statistical associations to many conditions.

This does not mean that it is a cause, but may indicate these bacteria prosper with the disruption associated with the condition. An example is below

Note that these are almost always present, it is when the percentile ranking exceeds 84%ile that we have a strong indicator which is illustrated below with two distributions. Note that the amount is small.

Unfortunately, restricting to genus level resulted in nothing.

Overview by symptom

This lists all of the symptoms found significant in various lab processing pipeline. The number depends on the number of samples contributed and the number of samples annotated with symptoms. This page is recomputed and updated on the 2nd of each month; more data means more associations.

Note Taxa identification is fuzzy and should never be assumed to be “correct”. The same FASTQ file processed thru ubiome, Ombre, Biomesight and Sequentia biotech; resulted in different genus being reported with different amounts. Clearly, the associations is processing pipeline dependent.

Genus identification

Looking at Immune Manifestations: Constipation we can compare results across different tests

We see the 3 are in consensus for Butyricimonas being increased and one is silent. We see 2 are in consensus for Lachnobacterium being increased, and two are silent (at the moment, waiting for more data). Two are in consensus for Desulfosporosinus being decreased with two silent.

The lab processing pipeline is very significant for detection rate (for Butyricimonas , one detects it 57% or the time and another lab 77% of the time) and the amount reported.

Technical Note: Microbiome Analysis is Fuzzier than a Peach with Mold!!

This is a post in this series !Technical Notes on Microbiome Analysis

The Question

A reader forwarded this study to me:

Accuracy of taxonomy prediction for 16S rRNA and fungal ITS sequences [2018]

While this paper is dealing with fungi the tables can be eye opening for some people. A suitable quote from the paper “When the accuracy of genus predictions was averaged over a representative range of identities with the reference database (100%, 99%, 97%, 95% and 90%), all tested methods had ≤50% accuracy on the currently-popular V4 region of 16S rRNA.“

My expertise is in statistics, operational research and artificial intelligence, with good expertise in reading medical studies; so I asked a colleague who has a Ph.D. in Molecular Genetics. His casual comments were:

There are several studies with ASVs out there. Especially the recent ones. Clustering pipeline is what matters here. But I agree that full length gives better taxonomic assignment.
Problem is full length is twice as expensive. So my point is when using V4, you will achieve incredibly better taxonomic assignments with ASV vs OTU. However, full length or V3-V5 gives a better resolution.

He also shared this graphic from Zymo Research. The V4 often cost around $50 and the full length can be 3-4x more.

What is ASV?

  • ASV stands for amplicon sequence variants.
  • OTU stands for operational taxonomic units

ChatGPT gives a good common man explanation:

Both methods aim to characterize and quantify the diversity of microorganisms in a given sample, but they differ in their underlying algorithms and conceptual frameworks.

  1. Amplicon Sequence Variants (ASVs):
    • ASVs are derived from high-throughput sequencing data by clustering sequences that differ by as little as a single nucleotide. This means that ASVs are defined at a very fine level of sequence resolution.
    • The goal of ASVs is to represent individual unique sequences within a dataset, thereby capturing the most detailed information about the microbial community present in a sample.
    • ASVs are typically generated using algorithms like DADA2 (Divisive Amplicon Denoising Algorithm 2), which infer exact sequence variants and correct sequencing errors.
    • ASVs are considered more accurate in capturing true biological diversity but may be more sensitive to sequencing errors.
  2. Operational Taxonomic Units (OTUs):
    • OTUs are clusters of similar sequences that are defined based on a chosen sequence similarity threshold (commonly 97% similarity for bacterial 16S rRNA gene sequences).
    • The 97% similarity threshold is often used to group sequences into OTUs to approximate the species level, although this can vary depending on the marker gene and research goals.
    • OTUs are generated using methods such as UCLUST, UPARSE, or others that involve sequence clustering. The resulting OTUs represent a consensus sequence for each cluster.
    • OTUs are considered more tolerant to sequencing errors, but they may group together closely related species or strains into the same cluster.

In summary, the main difference lies in the level of sequence resolution. ASVs aim for the highest possible resolution by identifying unique sequences, while OTUs represent clusters of similar sequences based on a chosen threshold. The choice between ASVs and OTUs depends on the specific research goals, the desired level of taxonomic resolution, and considerations related to sequencing error handling and computational resources.

To translate into human terms: ASV identifies criminals by fingerprints or DNA, while OTU identifies by the image from a security camera.

A Dilemma for Direct-To-Retail Tests

My colleague words makes the points clearly: Problem is full length is twice as expensive. Consumers are not knowledgeable about the differences but are very cost aware. The cheapest and least reliable way is often the norm. A direct to retail test costing less than $400 is likely to use the more inaccurate processes.

A Dilemma for Data from Studies

We encounter the same issue often for studies, budget! Searching the US National Library of Medicine for ASV, I get 2,955 results

Searching the US National Library of Medicine for OTU, I get 9,180 results. We also see that ASV is replacing OTU starting around 2021.

This means that many studies published before 2021 may have correctly identified the bacteria impacted as little as 50% of the time. So, does Barley increases or decreases Bifidobacterium?

In addition to possible confounders with selection of control and subjects in the study, we must now consider the possibility of misidentification of the bacteria. For myself and microbiome prescription’s expert system, this is not a major issue because we are using a fuzzy logic expert system. Suggestions are based on most probable given the data available.

Many medical practitioners (MDs and naturopaths) are not trained in this area and resort to a naïve deterministic approach.

Additional Suggested Literature

A comparison of bioinformatics pipelines for compositional analysis of the human gut microbiome [2023]

The differences of the same sample, Bacterial genera profile. Top 10 most abundant bacterial genera per pipeline resulted in a total of 16 unique genera.

Microbiome Analysis via OTU and ASV-Based Pipelines—A Comparative Interpretation of Ecological Data in WWTP Systems [2022]

  • Additional recent work has shown that individual pipelines themselves may be biased toward certain phyla [15,21]
  • The Illumina sequencing output reported an average quality of Q30 ≥ 81.9%.

Ranking the biases: The choice of OTUs vs. ASVs in 16S rRNA amplicon data analysis has stronger effects on diversity measures than rarefaction and OTU identity threshold [2021]

  • Based on mock communities, ASV-based approaches had a higher sensitivity in detecting the bacterial strains present, sometimes at the expense of specificity [17–20]
  • OTUs detected much higher amounts of Verrucomicrobiae in the seston and sediment samples than were detected by the ASV approach. These differences are surprising given that both OTU and ASV approaches classified sequences to the same database.

Bottom Line

In dealing with microbiomes in a clinical setting, we have multiple fuzziness:

  • The actual bacteria being reported (and the amount) is not reliable (in the common sense of that word), it is probable.
  • When trying to modify the microbiome, the impact on the reported bacteria is not reliable (in the common sense of that word), it is probable.

This means using a single study has significant risk. With a diverse collections of studies and facts, then a fuzzy logic expert system results in significantly reduced risk and a higher probability of successful manipulation. It also illustrates why the Large Language Model (i.e. ChatGPT style) is very inappropriate. and likely machine learning also.

As of this writing, Microbiome Prescription has 10,390 Citations from US National Library of Medicine resulting in 2,415,340 facts in it’s expert system.