A reader wrote:

There’s one thing I which caused some bewilderment though,  I put the screenshots from the recommendations from Biomesight here below, and I don’t understand why they seem quite divergent to what you are suggesting. I don’t know if it’s just my amateur eyes and then not so divergent after all, but to me they do seem quite different (apart from the lactobacilli). Shall I just ignore their suggestions ( also food wise) or would you say by and large it goes into the right direction? 

Reader, May 23,2024

The answer depends on the logic each provider uses, which bacteria are in their microscope that needs changes, depth of their research and their skills in addressing contradictory results. I will look at three providers below:

• Biomesight (provided by the reader)
• Vitract (from a review copy)
• Microbiome Prescription

See also this post: Why do metabolite levels disagree between sites?

Biomesight

We see a number by each suggestion

Hovering over the item will show the bacteria believed to be impacted

Clicking on the name will show details. Note that the bacteria shown is correct. The link also shows “Galactooligosaccharides (GOS)” and not the food suggested explicitly. The food selected contains GOS but none of the studies are explicitly for Beetroot. To MP, the beetroot contains multiple compounds, some may have overpowering negative effects — hence MP keeps to precisely what is cited in the study.

My inferred take-away from looking at the suggestions

• Foods and substances are done by association and inference
• Only a handful of bacteria are considered.

Consider the bacteria list on MP for the same substance – 1757 citations at the moment.

Vitract

This is from an early draft. They are using the database of Microbiome Prescription but with a set of proprietary rules and algorithms. For the bacteria in their scope, MP has no contraindicated data and do not use inferences to parent or child taxa. That is, there is no need for balance algorithms. In short, it is a proprietary suggestion system designed by a Ph.D. in Molecular Genetics with a number of M.Sc. (for example, Bioinformatics) and Ph.D. Candidates (Nutrition), in consultation with MDs, NDs and Dieticians.

Microbiome Prescription

For details on which bacteria are selected, see Algorithm for “Just Give Me Suggestions”. Typically we have an average of 65 bacteria under our microscope with 600 on some shotgun samples. Roughly 20-30% of the bacteria identified.

Now for every suggestion we make available the list of studies (137 for this probiotic suggestion). Note in the study names — that this probiotic is explicitly named.

We also include the negative effects

We have our own proprietary algorithm on how to evaluate this data. People can take this data and apply their own logic.

MP’s goal is to be the most comprehensive source with new studies adding every week. We have also been delighted that Vitract (who I have been doing pro-bono consultation with) have set a team of their M.Sc. (or higher) staff on checking the citations. They have been finding a very low bad entry rate ( < 1%).

Bottom Line

• What is the scope of their microbiome scope? IMHO: the bigger the scope, the better the results
• Is the data based on explicit studies or on interference (A contain X and X helps — we’ll ignore B,C,D that is also in X)
  • BEWARE of sites that do not provide explicit studies – often they are working from hearsay.
• Does the suggestion consider contraindicated information?
• How big a database are they using? Have there been third party checking of the database?

Suggestions may be reasonable: a professional dietician would likely do the same logic in the case of BiomeSight suggestions.

Questions

• Since Vitract and Microbiome Prescription use the same database, will suggestions always agree?
  • No, for several reasons:
    • The bacteria in-scope-to-change are different. If MP picks one that Vitract does not, then suggestions may shift for some substances. Vitract computes its own definitions of what is high and low.
    • Vitract hand select certain studies to be excluded or lessen in values. Studies may be on human, animals or a lab situation (petri dish) – they wanted to weight the value of each study different from MP.
• What should I do if there are explicit disagreements?
  • The safest path is to do only things that there is agreement on.
  • If another item interests you, review the studies cited to make a decision.

Backstory

I had no gut problems and only minor health niggles before Covid. I have been hypothyroid for 20 years.

After three rounds of covid (but no vaccines) I have burning and tingling parasthesias in my extremities, neuropathy in my face, plus gut pain, lots of hair loss, and I feel cold a lot and sleep poorly. Some fatigue and shortness of breath, but the other symptoms are much worse.

Trying to increase my bifido and lactobacillus via suggestions on biomesight has barely moved the needle.

All my blood tests work has been normal from a year ago, although now I have a weakly postiive ANA test result.

Analysis

We have 2 samples: 2023-11-20 and 2024-04-26. Both samples are very similar.

High Level Overview

• “Leaked” from Oral Cavity: By volume 77%ile, prior 70%ile
  • Dialister invisus 31%ile, 88%ile
  • Pedobacter 98%ile, prior 90%ile
  • Suggested reading: The Benefits of Probiotics on Oral Health: Systematic Review of the Literature [2023]
• General Health Predictors: 10 out of range, prior 11 out of range.

Looking at the “smoking gun”, Pedobacter, we found no known factors to reduce it 🙁

Quick Summary; Past action plan has “barely moved the needle.”

Going Forward

The usual “just give me suggestions” with one addition Bifido and lactobacillus are her primary concern, so I will hand picked those on both samples. and get an emphasis for thoses. We see that one went up and one went down.

Bacteria	2024	2023
Lactobacillus (only Lactobacillus iners)	38%ile	NONE
Bifidobacterium	8%ile	39%ile

We then do a Uber Consensus with BOTH samples (since they are similar) with a total of 11 sets of suggestions.

• All 11 agrees on these:
  • bifidobacterium animalis lactis (probiotics)
  • vitamin a
  • Olive Oil
  • barley
  • lactobacillus brevis (probiotics)
  • clostridium butyricum (probiotics),Miya,Miyarisan
  • ginger and rosemary
• Items to be avoided on all 11 are below
  • lactobacillus gasseri (probiotics)
  • chitosan,(sugar)
  • vegetarians
  • blackcurrant
  • Dextrin
  • Guaiacol (polyphenol)
    

I looked at the interaction charts, the first one is for Lactobacillus and noticed high (99%ile) for Rickettsia and for Heliobacter (61%ile). The last one suggests testing for Helicobacter pylori should be discussed with their MD.

The chart for bifidobacterium shows many of the same bacteria that will surpress bifidobacterium. Note that lactobacillus (top right) is indicated as surpressing bifidobacterium; this agrees with the above numbers.

This appears to illustrate that being focused on just one or two bacteria may not be the best path. A holistic approach (looking at what changes all of the bacteria above may be a critical step of improving things).

Antibiotic path

Long COVID is very similar to ME/CFS. Looking at antibiotics suggestions, about 60% of them are commonly use bt ME/CFS specialists. These areL

• metronidazole (antibiotic)s[CFS]
• ciprofloxacin (antibiotic)s[CFS]
• clindamycin (antibiotic)s[CFS]
• minocycline (antibiotic)s[CFS]
• ampicillin (antibiotic)s[CFS]
  

My personal preference would be one round of metronidazole, a three week break then minocycline, another break and then one of the other ones. This is following Dr. Jadin’s Current Protocol for ME/CFS using antibiotics

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.

Back Story

I’m at the end if my rope and need help. I’m at my wits end with:

• mcas and
• mcs.

I was hit by levaquin in 1/14/20. It killed off my microbiome 22 days later reactions started. I believe has Sibo since then but was confirmed 4/23 and 4/24: Methane and hydrogen

I started raw milk one year ago and was able to stop food and scent reactions I was 85% better until March when dryer sheets on someone I m home set me off then a true anaphylactic event on 4/1 needing epi pen. Since raw milk I developed sulphur intolerance

I’m miserable and like ready for assisted suicide… but not seriously. I can’t deal with it anymore the ecoli albertii is way high 97% higher than everyone who took Biomesight so is methanobacter smithii I can’t tolerate any of the sulphur products since raw milk over grew stuff making me sulphur sensitive to microbes releasing sulphur. I never had issues with sulphur before raw milk one year ago!!!! I used to soak in Epsom all the time and eat garlic and broccoli like crazy that all stopped with this over growth!!!

My mast cell reactions and brain fog are once again bad. I do have mthfr do it’s hard to detox not sure that matters

Initial Analysis

As a start point, this has the lowest eubiosis that I have reviewed. Eubiosis is a computation on the chart below it. We see a lot of different species at abnormally high levels. A balance gut would have all of the blue lines close to the red lines.

There are a number of these bacteria that are strongly associated statistically with different symptoms.

I added the symptoms cited and went over to the new “Symptoms associations to Taxon, Compounds and Enzymes” to give this new feature an actual data case.

Comorbid: Multiple Chemical Sensitivity

• All 46 significant bacteria were high (over 95%)
• 36 Compounds were out of whack – some high and some low
• 21 Enzymes: 8 too low and 13 too high. One was connected to a Vitamin, B6. pyridoxal 5&prime;-phosphate synthase (glutamine hydrolysing) so supplementation of B6 (50-200 mg/day) should be considered. – this is associated with several symptoms.

Checking Enzymes for other conditions for possible vitamin impact.

• sulfide-dependent adenosine diphosphate thiazole synthase  is 95%ile. so avoid Vitamin B1 (i.e. no B-Complex) – this is associated with several symptoms.

Oral Bacteria Leakage

Looking at this new feature, we see three bacteria that stand out.

I did a hand-picked suggestions on just these three to see what can likely be done:

• Good Oral Hygene
• VItamins to dissolve in the mouth
  • vitamin b2,Riboflavin
  • Vitamin B1
• Probiotics to dissolve in warm water, hold in the mouth and then gargle with (at least 90 minutes away from eating)
  • The Benefits of Probiotics on Oral Health: Systematic Review of the Literature – PMC (nih.gov)[2023]
  • lactobacillus salivarius – long history for oral use
  • Lactobacillus jensenii
  • DO NOT USE:
    • lactobacillus plantarum
    • bacillus subtilis
    •  bifidobacterium longum
    • Olive Oil
  • Symbioflor-1, although not in the list, it should be consider, see Symbioflor® 1 – Respiratory diseases | SymbioPharm

I went to another person that used the same lab that I know with both of these conditions and we see something in common

The LLM comment stated: Metabolic Interactions: Some Veillonellaceae bacteria, including Dialister species, are known for their metabolic interactions with other bacteria in the microbiota. They can metabolize certain compounds produced by other bacteria…

• Dialister invisus sp. nov., isolated from the human oral cavity [2003]
• Microbiological Aspects of Root Canal Infections and Disinfection Strategies: An Update Review on the Current Knowledge and Challenges [2021]
• Characterization of Dialister species in infected root canals [2006]
• The nasal microbiome in asthma [2018] Four species were differentially abundant based on asthma status after correction for multiple comparisons: Dialister invisus …

Going Forward

I am going to do “Just give me Suggestions include Symptoms” with the revised algorithm (see Algorithm for “Just Give Me Suggestions”) . I could have hand picked each bacteria associated with symptoms, but given the number of very high, this would likely produce similar effect with less effort.

This results in the Consensus having 7 sets of suggestions

Suggestions To Take

The top, non-prescription items are below. It is full of spices and herbs with just one vitamin and one probiotic.

Modifier

cinnamon (oil. spice)

oregano (origanum vulgare, oil)

vitamin b2,Riboflavin

thyme (thymol, thyme oil)

nigella sativa seed (black cumin)

garlic (allium sativum)

foeniculum vulgare,fennel

rosmarinus officinalis,rosemary

green tea

Hesperidin (polyphenol)

vegetable/fruit juice-based diets

naringenin(grapefruit) (Flavonoid)

neem

lactobacillus kefiri (NOT KEFIR)

peppermint (spice, oil)

syzygium aromaticum (clove)

triphala

Looking at probiotics, we have a good number that would allow easy rotation of probiotics. Two are usually difficult to obtain: lactobacillus kefiri and lactobacillus sakei . Most are available at my usual two preferred sources: Custom Probiotics and Indian Bulk Exporter (Maple Life Sources). See this list for sources not available there. By rotation, I mean 20-50 BCFU daily of one probiotic for 2 weeks and then change to another probiotic.

lactobacillus kefiri (NOT KEFIR)

lactobacillus casei (probiotics) [CB,MLS]

lactobacillus sakei (probiotics)

lactobacillus salivarius (probiotics) [CB,MLS]

lactobacillus reuteri (probiotics) [CB,MLS]

bifidobacterium infantis,(probiotics) [CB,MLS]

enterococcus faecium (probiotic)

lactobacillus paracasei (probiotics) [CB,MLS]

clostridium butyricum (probiotics),Miya,Miyarisan

Items to Reduce or Avoid

The top items are below. In relationship to the take, it seems clear that spices and herbs may be critical — increasing vegetables may have limited benefit. Spices and herbs can be done as capsules, teas, oils or just putting on food.

Modifiers To Avoid

resistant starch

Slippery Elm

ß-glucan

arabinogalactan (prebiotic)

chestnut tannins

Pork

rice bran

aspartame (sweetner)

quercetin,resveratrol

navy bean

vitamin B3,niacin

high fiber diet

partially hydrolyzed guar gum

Bofutsushosan

Pumpkin

moderate-protein moderate-carbohydrate

resistant maltodextrin

The question of milk came up. AVOID . If you need a milk like substance, use Soy milk only – other milks will contain milk sugar.

• Cow milk 4mg per 100ml
• Goat milk 0.6mg per 100ml
• Soy milk 0mg per 100ml

Bottom Line

This is an interesting sample, the very high number of high percentile bacteria (with corresponding low Eubiosis) present some challenges. The interesting thing is that just targeting the high percentile ones produce a similar set of suggestions as the “Just Give Me Suggestions”. The item that is interesting is the massive number of different herbs at the top of the list. With the Oral Bacteria leakage issue, strive to take them as teas.Caffeine is a weak to be avoided, so it looks like herb teas (without caffeine — i.e. not black teas with herbs, just pure herbs) will be the regular beverage.

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.

This person is a long time ME/CFSer. I should start by pointing out that the Eubiosis measure is easy to misinterpret. This person has a good 90.2% eubiosis. This indicates that things are more even (balance is likely a poor choice of word, too many meanings attached) — this is not a health measure as such. It’s a statistical measure whether the microbiome is matching the ideal pattern (not health specific).

Health Analysis is health orientated. Looking at those values we see a loss of health indicators while the evenness has improved.

1. “Leaked” from Oral Cavity
   • By Taxa is 70%ile, was 48%ile (7/2023), 70% (09/2022)
   • By Volume 49%ile, was 19% (7/2023) , 38.5 (09/2022)
2. Jason Criteria: 17%ile was 17%ile the same
3. Key Symptoms bacteria went to 18 was 12

The Oral Cavity stands out as a concerning factor for this person.

Analysis

We have a historic trend of 6 samples. We need to be careful of our interpretation because of differences in Lab Read Quality. The Lab Read Quality bounces around, and with that, other values may echo these shifts (i.e. up to 20% shifts for some measures). A low read quality means less bacteria are reported, for example, when it was low, the Outside Kaltoft-Moldrup has low, when it was high, the value became high.

Another way to view it is this: If 10% are out of range and 850 are reported then we have 85. If we have 500 in another report then we would expect 50. This could be misread as a 85/50 or a 70% increase in out of range bacteria. Technically, it is more complicated but that should explain the problem.

We have only one item 🙂 that is a clear improvement and one item suggesting a loss :-(.

Criteria	1/5/2024	7/3/2023	9/26/2022	1/9/2022	3/8/2021	7/26/2020
Eubiosis	91.5	68.8	41.1	65.6	31.5	43.5
Lab Read Quality	7.9	4.4	11	3.3	3.6	3
Outside Range from GanzImmun Diagostics	15	15	19	19	13	13
Outside Range from JasonH	4	4	5	5	6	6
Outside Range from Lab Teletest	21	21	18	18	27	27
Outside Range from Medivere	16	16	17	17	13	13
Outside Range from Metagenomics	5	5	7	7	8	8
Outside Range from Microba Co-Biome	2	2	2	2	2	2
Outside Range from MyBioma	10	10	3	3	9	9
Outside Range from Nirvana/CosmosId	22	22	18	18	20	20
Outside Range from Thorne (20/80%ile)	215	215	224	224	228	228
Outside Range from XenoGene	36	36	35	35	37	37
Outside Lab Range (+/- 1.96SD)	7	14	2	10	11	26
Outside Box-Plot-Whiskers	55	49	46	73	92	103
Outside Kaltoft-Moldrup	114 🙁	72	84	47	38	86
Bacteria Reported By Lab	749	545	838	495	660	483
Bacteria Over 90%ile	23 🙂	47	34	66	69	100
Bacteria Under 10%ile	49	28	21	11	2	44
Shannon Diversity Index	1.958	1.172	1.595	1.491	1.97	0.933
Simpson Diversity Index	0.041	0.234	0.075	0.128	0.045	0.012
Chao1 Index	16554	7002	18614	6127	11112	7513
Pathogens	32	25	34	29	28	23
Condition Est. Over 90%ile	0	0	0	0	0	0
Actual Symptoms in top 10 Forecasted	n/a	5	n/a	3	5	8

We have a good number of bacteria strongly statistically associated with symptoms

The difference between the two symptom forecast methods is shown below. The newer method (genus only) appears to predict symptoms better

Going Forward

With the revised algorithm (see Algorithm for “Just Give Me Suggestions” with symptoms we get the following. Unlike many samples, there were few antibiotics at the top of the list.  

To Take

Spices and herbs can be done as capsules, teas, oils or just putting on food, but given the Oral leakage — as teas should be considered.

Modifier

whey

raffinose(sugar beet)

lactobacillus casei (probiotics)

fructo-oligosaccharides (prebiotic)

rosmarinus officinalis,rosemary

garlic (allium sativum)

lactobacillus paracasei (probiotics)

vitamin b2,Riboflavin

Lactobacillus Johnsonii (probiotic)

peppermint (spice, oil)

bifidobacterium longum bb536 (probiotics)

Cacao

trametes versicolor(Turkey tail mushroom)

lactobacillus reuteri (probiotics)

chondrus crispus,red sea weed

Dangshen

jerusalem artichoke (prebiotic)

lactobacillus sakei (probiotics)

lauric acid(fatty acid in coconut oil,in palm kernel oil,)

lactobacillus kefiri (NOT KEFIR)

green tea

foeniculum vulgare,fennel

Looking at probiotics, we have a good number that would allow easy rotation of probiotics. Two are usually difficult to obtain: lactobacillus kefiri and lactobacillus sakei . Most are available at my usual two preferred sources: Custom Probiotics and Indian Bulk Exporter (Maple Life Sources). See this list for sources not available there. By rotation, I mean 20-50 BCFU daily of one probiotic for 2 weeks and then change to another probiotic.

lactobacillus kefiri (NOT KEFIR)

lactobacillus casei (probiotics) [CB,MLS]

lactobacillus sakei (probiotics)

lactobacillus reuteri (probiotics) [CB,MLS]

bifidobacterium infantis,(probiotics) [CB,MLS]

bifidobacterium longum bb536 (probiotics)

lactobacillus paracasei (probiotics) [CB,MLS]

Lactobacillus Johnsonii [MLS]

Modifier To Avoid

saccharin

Ferric citrate (iron)

stevia

polydextrose

Pork

Slippery Elm

l-citrulline

nuts

Psyllium (Plantago Ovata Husk)

vegetarians Top of Form Bottom of Form

fibre-rich macrobiotic ma-pi 2 diet

Pulses

xylan (prebiotic)

Oral Bacteria Issue

This may be a likely contributor to ongoing issues. Why? the sinus and oral cavity repopulates the gut and undo prior improvements. My best suggestions are to address this are:

• When possible, drink teas with the any of the suggested herbs.
• Do not take probiotics as capsules, instead as powder dissolved in warm water and hold in the mouth before swallowing. See Symbioflor® 1 – Respiratory diseases | SymbioPharm, this may help.
• Address any dental issues

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.

This is a follow up to Technical Note: Identifying Key Bacteria to Address, part of this series Technical Notes on Microbiome Analysis. I am working with a new EU based start-up Precision Biome and in refining their algorithms they asked me to identify the key genus that should be considered (and other information).

The table below shows the top results that may be of interest in a clinical setting.

• Occurrences is the number of times it was detected as statistically significant.
• We averaged Chi² to provide more generic detection.
• [Shift] indicates if Chi² is for the low range test or the high range test.
  • Low with High Count indicates that the absence of cells is more severe in the low range than than the abundance of cells in the top range.
  • Often there is a shift to upper, resulting in over population of the top range and almost complete disappearance of the low range.
• Majority of the results were from 16s processing (with the inherent risk of misidentification)
• Contrary to common belief, low levels seems to be rarely the apparent cause, they may be a consequence of multiple highs.
• The data below can be replicated from data at https://citizenscience.microbiomeprescription.com/ (Open data) with the processes referred to above.

taxon	Tax Name	Shift	Occurrences	Average Chi2	Density
84567	Pedobacter	Low	355	127.9	High Count
114627	Alkaliphilus	Low	356	127.7	High Count
33951	Acetobacterium	Low	358	126.6	High Count
190972	Sedimentibacter	Low	353	126.4	High Count
1769729	Hathewaya	Low	362	126.4	High Count
100883	Coprobacillus	Low	360	125.4	High Count
28453	Sphingobacterium	Low	350	123	High Count
970	Selenomonas	Low	353	120.1	High Count
44000	Caldicellulosiruptor	Low	352	120	High Count
1378	Gemella	Low	353	119.3	High Count
82373	Anaerovibrio	Low	350	117.6	High Count
281119	Candidatus Amoebophilus	Low	352	117.2	High Count
29548	Rhodothermus	Low	348	115.2	High Count
69894	Tindallia	Low	347	110.1	High Count
864	Pectinatus	Low	351	108.1	High Count
33926	Candidatus Phytoplasma	Low	340	107.1	High Count
256319	Chlorobaculum	Low	348	106.4	High Count
89958	Natronincola	Low	332	105.1	High Count
2304693	Pseudoclostridium	Low	346	104.9	High Count
561	Escherichia	Low	345	103.6	High Count
1647	Erysipelothrix	Low	354	103.6	High Count
2093	Mycoplasma	Low	345	103.5	High Count
46205	Pseudobutyrivibrio	Low	587	103.4	High Count
94008	Thermicanus	Low	338	103.2	High Count
156973	Dysgonomonas	Low	345	102.1	High Count
119852	Oscillospira	Low	569	101.6	High Count
1263	Ruminococcus	Low	669	100.8	High Count
2316020	Mediterraneibacter	Low	670	100.7	High Count
33042	Coprococcus	Low	670	100.5	High Count
42447	Anaerobranca	Low	328	99.7	High Count
1350	Enterococcus	Low	264	99.3	High Count
35829	Acetivibrio	Low	664	97.6	High Count
1730	Eubacterium	Low	667	96.6	High Count
44260	Moorella	Low	254	96.3	High Count
376469	Olivibacter	Low	198	96.1	High Count
2740	Peptococcus	Low	543	95.2	High Count
131079	Limnobacter	Low	151	95.2	High Count
52784	Anaerofilum	Low	526	94.4	High Count
44258	Caloramator	Low	629	93.8	High Count
572511	Blautia	Low	897	93.3	High Count
816	Bacteroides	Low	897	93.2	High Count
841	Roseburia	Low	897	93	High Count
1485	Clostridium	Low	896	92.8	High Count
43994	Johnsonella	Low	618	92.8	High Count
265975	Oribacterium	Low	661	92.7	High Count
216851	Faecalibacterium	Low	897	92.7	High Count
909656	Phocaeicola	Low	895	92.6	High Count
1301	Streptococcus	Low	894	92.4	High Count
189330	Dorea	Low	897	92.4	High Count
28050	Lachnospira	Low	884	92.3	High Count
35832	Bilophila	Low	558	91.5	High Count
375288	Parabacteroides	Low	887	91.5	High Count
906	Megasphaera	Low	559	90.5	High Count
140625	Lachnobacterium	Low	634	88.6	High Count
1678	Bifidobacterium	Low	869	88	High Count
244127	Anaerotruncus	Low	867	87.3	High Count
207244	Anaerostipes	Low	893	86.4	High Count
838	Prevotella	Low	859	85.9	High Count
40544	Sutterella	Low	839	85.2	High Count
84108	Slackia	Low	508	83.8	High Count
29465	Veillonella	Low	842	83.6	High Count
1578	Lactobacillus	Low	870	82.2	High Count
162289	Peptoniphilus	Low	852	81.8	High Count
283168	Odoribacter	Low	857	80.6	High Count
61170	Holdemania	Low	860	79.5	High Count
102106	Collinsella	Low	853	79.3	High Count
33024	Phascolarctobacterium	Low	853	77.6	High Count
447020	Adlercreutzia	Low	473	76.5	High Count
1508657	Ruminiclostridium	Low	436	75.5	High Count
724	Haemophilus	Low	451	74.5	High Count
239934	Akkermansia	Low	824	74.3	High Count
86331	Mogibacterium	Low	841	73.5	High Count
872	Desulfovibrio	Low	806	72.6	High Count
836	Porphyromonas	Low	813	70.3	High Count
84111	Eggerthella	Low	767	69.6	High Count
574697	Butyricimonas	Low	779	69	High Count
1266	Sarcina	Low	228	68.8	High Count
1407607	Fusicatenibacter	Low	535	68.2	High Count
1506553	Lachnoclostridium	Low	314	68.1	High Count
292632	Subdoligranulum	Low	537	68	High Count
1505663	Erysipelatoclostridium	Low	540	67.7	High Count
1506577	Tyzzerella	Low	314	67.5	High Count
577309	Paraprevotella	Low	412	67.4	High Count
946234	Flavonifractor	Low	540	67.3	High Count
239759	Alistipes	Low	540	66.9	High Count
1654	Actinomyces	Low	718	66.9	High Count
43996	Catonella	Low	312	66.5	High Count
459786	Oscillibacter	Low	537	66.3	High Count
1769729	Hathewaya	High	270	66.2	High Count
1392389	Intestinimonas	Low	531	65.7	High Count
84567	Pedobacter	High	267	65.7	High Count
1649459	Hungatella	Low	311	65.5	High Count
33951	Acetobacterium	High	270	65.5	High Count
114627	Alkaliphilus	High	272	65.3	High Count
1164882	Lachnoanaerobaculum	Low	313	65.3	High Count
2048137	Agathobaculum	Low	312	65.3	High Count
698776	Cellulosilyticum	Low	308	64.8	High Count
2039240	Anaerotignum	Low	311	64.6	High Count
100883	Coprobacillus	High	277	64.4	High Count
190972	Sedimentibacter	High	268	64.1	High Count
52784	Anaerofilum	High	291	64	High Count
2569097	Anaerobutyricum	Low	309	63.6	High Count
1774128	Murimonas	Low	303	63.5	High Count
2740	Peptococcus	High	282	63.4	High Count
2719313	Enterocloster	Low	309	63.3	High Count
28453	Sphingobacterium	High	267	63.1	High Count
970	Selenomonas	High	259	62.7	High Count
1427378	Acetatifactor	Low	304	62.5	High Count
44000	Caldicellulosiruptor	High	256	61.7	High Count
1378	Gemella	High	269	61.4	High Count
204475	Gemmiger	Low	300	61.2	High Count
119852	Oscillospira	High	333	61.1	High Count
29548	Rhodothermus	High	258	60.8	High Count
281119	Candidatus Amoebophilus	High	253	60.5	High Count
82373	Anaerovibrio	High	257	59.8	High Count
1505657	Intestinibacter	Low	488	59.7	High Count
248744	Marvinbryantia	Low	502	59.4	High Count
253238	Ethanoligenens	Low	303	59.1	High Count
46205	Pseudobutyrivibrio	High	371	58.9	High Count
241189	Hespellia	Low	519	58.3	High Count
69894	Tindallia	High	252	57.7	High Count
864	Pectinatus	High	259	57.5	High Count
89958	Natronincola	High	253	57.4	High Count
43994	Johnsonella	High	346	57.4	High Count
131079	Limnobacter	High	140	57.3	High Count
1843210	Anaerocolumna	Low	293	56.8	High Count
44249	Paenibacillus	Low	297	56.7	High Count
1481960	Peptoclostridium	Low	208	56.7	High Count
94008	Thermicanus	High	253	56.6	High Count
84108	Slackia	High	271	56.6	High Count
577310	Parasutterella	Low	501	56.5	High Count
830	Butyrivibrio	Low	499	56.4	High Count
906	Megasphaera	High	315	56.4	High Count
44258	Caloramator	High	355	56.2	High Count
256319	Chlorobaculum	High	247	56.1	High Count
437755	Moryella	Low	497	56.1	High Count
1647	Erysipelothrix	High	255	56	High Count
33926	Candidatus Phytoplasma	High	244	56	High Count
561	Escherichia	High	247	55.9	High Count
2304693	Pseudoclostridium	High	249	55.9	High Count
33042	Coprococcus	High	438	55.5	High Count
1505652	Terrisporobacter	Low	504	55.5	High Count
1569	Sporosarcina	Low	294	55.5	High Count
35829	Acetivibrio	High	410	55.3	High Count
2316020	Mediterraneibacter	High	441	55.2	High Count
376469	Olivibacter	High	181	55.1	High Count
2093	Mycoplasma	High	251	54.6	High Count
588605	Robinsoniella	Low	294	54.6	High Count
156973	Dysgonomonas	High	258	54.6	High Count
35832	Bilophila	High	319	54.5	High Count
1263	Ruminococcus	High	456	54.5	High Count
1562	Desulfotomaculum	Low	283	54.5	High Count
838	Prevotella	High	447	54.3	High Count
140625	Lachnobacterium	High	348	54.1	High Count
1350	Enterococcus	High	221	54.1	High Count
44748	Sporobacter	Low	493	54	High Count
42447	Anaerobranca	High	242	53.8	High Count
40544	Sutterella	High	444	53.3	High Count
162289	Peptoniphilus	High	428	53.1	High Count
1485	Clostridium	High	536	53	High Count
909656	Phocaeicola	High	541	52.9	High Count
572511	Blautia	High	545	52.8	High Count
816	Bacteroides	High	548	52.8	High Count
44260	Moorella	High	212	52.6	High Count
189330	Dorea	High	546	52.6	High Count
841	Roseburia	High	552	52.5	High Count
1017280	Pseudoflavonifractor	Low	490	52.4	High Count
39948	Dialister	Low	498	52.3	High Count
265975	Oribacterium	High	419	52.3	High Count
216851	Faecalibacterium	High	563	52.3	High Count
1678	Bifidobacterium	High	492	52.1	High Count
29465	Veillonella	High	450	52.1	High Count
66831	Facklamia	Low	275	52	High Count
244127	Anaerotruncus	High	480	52	High Count
1730	Eubacterium	High	462	51.9	High Count
375288	Parabacteroides	High	539	51.9	High Count
1301	Streptococcus	High	564	51.9	High Count
28050	Lachnospira	High	555	51.6	High Count
1501226	Romboutsia	Low	480	51.3	High Count
379899	Niabella	Low	292	51.3	High Count
1432051	Eisenbergiella	Low	485	50.5	High Count
579	Kluyvera	Low	208	50	High Count
1578	Lactobacillus	High	475	49.9	High Count
283168	Odoribacter	High	456	49.6	High Count
653683	Anaerosporobacter	Low	209	49.6	High Count
724	Haemophilus	High	266	49.4	High Count
207244	Anaerostipes	High	549	49.3	High Count
61170	Holdemania	High	446	49.3	High Count
404402	Howardella	Low	268	49.2	High Count
872	Desulfovibrio	High	395	48.7	High Count
1433991	Brassicibacter	Low	270	48.6	High Count
86331	Mogibacterium	High	396	48.6	High Count
836	Porphyromonas	High	390	48.4	High Count
33024	Phascolarctobacterium	High	439	48.2	High Count
1508657	Ruminiclostridium	High	285	48.1	High Count
2282743	Desulfohalotomaculum	Low	269	47.9	High Count
239934	Akkermansia	High	407	47.7	High Count
397864	Barnesiella	Low	476	47.6	High Count
447020	Adlercreutzia	High	247	47.3	High Count
150022	Finegoldia	Low	484	47.3	High Count
1470353	Candidatus Soleaferrea	Low	201	47.1	High Count
102106	Collinsella	High	478	46.7	High Count
577309	Paraprevotella	High	243	46.4	High Count
420345	Lactonifactor	Low	451	46.3	High Count
596767	Hydrogenoanaerobacterium	Low	441	45.8	High Count
2529408	Schaalia	Low	202	45.4	High Count
574697	Butyricimonas	High	381	45	High Count
1654	Actinomyces	High	361	45	High Count
84111	Eggerthella	High	394	44.3	High Count
177971	Shuttleworthia	Low	434	42.5	High Count
1870884	Clostridioides	Low	193	42.5	High Count
644652	Gordonibacter	Low	200	41.7	High Count
191303	Turicibacter	Low	190	41.6	High Count
292632	Subdoligranulum	High	258	40.2	High Count
1716	Corynebacterium	Low	202	40	High Count
1407607	Fusicatenibacter	High	260	39.9	High Count
946234	Flavonifractor	High	256	39.9	High Count
459786	Oscillibacter	High	251	39.8	High Count
1392389	Intestinimonas	High	247	39.3	High Count
1505663	Erysipelatoclostridium	High	279	39.1	High Count
1506577	Tyzzerella	High	161	39.1	High Count
44748	Sporobacter	High	163	38.5	High Count
239759	Alistipes	High	283	38.4	High Count
830	Butyrivibrio	High	181	38.2	High Count
1164882	Lachnoanaerobaculum	High	158	38.1	High Count
43996	Catonella	High	162	37.9	High Count
1649459	Hungatella	High	155	37.9	High Count
698776	Cellulosilyticum	High	154	37.8	High Count
241189	Hespellia	High	205	37.6	High Count
2048137	Agathobaculum	High	151	37.4	High Count
1774128	Murimonas	High	145	37.4	High Count
100175	Papillibacter	Low	194	37.3	High Count
2039240	Anaerotignum	High	148	37.3	High Count
2569097	Anaerobutyricum	High	142	37.2	High Count
1506553	Lachnoclostridium	High	191	37	High Count
2719313	Enterocloster	High	145	36.8	High Count
596767	Hydrogenoanaerobacterium	High	148	36.8	High Count
237	Flavobacterium	Low	168	36.3	High Count
1505657	Intestinibacter	High	210	36.3	High Count
437755	Moryella	High	174	36.2	High Count
1427378	Acetatifactor	High	147	36.1	High Count
577310	Parasutterella	High	191	35.9	High Count
253238	Ethanoligenens	High	132	35.8	High Count
165779	Anaerococcus	Low	194	35.7	High Count
248744	Marvinbryantia	High	204	35.4	High Count
204475	Gemmiger	High	145	34.9	High Count
39948	Dialister	High	161	34.9	High Count
397864	Barnesiella	High	124	34.6	High Count
420345	Lactonifactor	High	115	34.5	High Count
1017280	Pseudoflavonifractor	High	157	34.4	High Count
1505652	Terrisporobacter	High	190	34.2	High Count
177971	Shuttleworthia	High	120	34.2	High Count
588605	Robinsoniella	High	116	34	High Count
1432051	Eisenbergiella	High	167	34	High Count
1569	Sporosarcina	High	122	33.7	High Count
44249	Paenibacillus	High	126	33.7	High Count
1843210	Anaerocolumna	High	128	33.6	High Count
168934	Thalassospira	Low	176	33.6	High Count
1501226	Romboutsia	High	165	33	High Count
150022	Finegoldia	High	130	32.8	High Count
1562	Desulfotomaculum	High	109	32.6	High Count
66831	Facklamia	High	104	31.6	High Count
1348911	Coprobacter	Low	194	31.4	High Count
379899	Niabella	High	110	31.3	High Count
135858	Catenibacterium	Low	169	28.9	High Count
1472649	Dielma	Low	180	28	High Count
117563	Granulicatella	Low	162	26.3	High Count
172900	Victivallis	Low	157	26.3	High Count
194	Campylobacter	Low	181	26.1	High Count
109326	Anaerovorax	Low	155	25.7	High Count
184869	Varibaculum	Low	178	24.7	High Count
580024	Enterorhabdus	Low	167	24.5	High Count
963	Herbaspirillum	Low	159	24.4	High Count
1357	Lactococcus	Low	157	23.8	High Count
1161127	Murdochiella	Low	154	22.2	High Count
189326	Gelria	Low	149	20.7	High Count
1473205	Senegalimassilia	Low	135	20.4	High Count

A reader forward this image from BiomeSight to me:

Apart from wording being questionable (former technical writer speaking) because many people will read it as needing to be increased whereas the chart on the right clearly shows that it needs to be decreased.

Same sample on MP reports:

• D-Lactic Acid 18%ile. Thus much lower than the mid point! A Contradiction! D-Lactic acid is the bad form of lactic acid. L-Lactic acid is the very good form!

A brief discussion of how metabolites are estimated. There are several approaches used by retail providers:

• Based on clinical studies reporting that a certain bacteria produces this compound.
  • Then just total up the count of all such bacteria
• Based on clinical studies reporting that a certain bacteria produces this compound AND the amount that each produces.
  • Then just total up the count times the amount of all such bacteria
• Based on KEGG: Kyoto Encyclopedia of Genes and Genomes and derive the average amount per species (and/or genus)
  • Then just total up the count times the amount of all such bacteria
  • This is the method that Microbiome Prescription [MP] uses.

There are additional methods but most are significantly more expensive. Working from clinical studies always have the issue of some bacteria not being studies – hence estimates may be off.

Example of one metabolite (Reuterin) showing different amounts per bacteria according to strains

From prediction to function using evolutionary genomics: human-specific ecotypes of Lactobacillusreuteri have diverse probiotic functions[2014].

Bottom Line

There is no “right” answer. You should ask the provider of the estimates exactly how are metabolites computed (and data sources). In the case of MP, the source and method are clearly identified above. Additionally, the site should provide some education on the significance of each. Often metabolites are requested by customers and the provider does an “economical” analysis and implementation to satisfy the customer request; the results may be less than ideal or complete.

Often education is needed. The reader that emailed me, asked “should I not stop all lactate/lactic acid producing probiotics“. NO…. because L-Lactic acid is good and inhibits bad bacteria. So I checked L-Lactate (commonly just called Lactate) – see below.

Description on MP of this Metabolite

1. D-Lactic Acidosis: Elevated levels of D-lactic acid in the blood can lead to a condition known as D-lactic acidosis. This occurs when the body’s ability to metabolize D-lactic acid is impaired or overwhelmed. It’s often associated with specific conditions such as short bowel syndrome (SBS) or other gastrointestinal disorders where there’s an increase in the production and absorption of D-lactic acid.
2. Neurological Symptoms: D-lactic acidosis can lead to neurological symptoms, including confusion, impaired cognitive function, difficulty concentrating, and altered mental status. Severe cases may even lead to coma.
3. Gastrointestinal Symptoms: Symptoms such as abdominal pain, diarrhea, and bloating can occur in individuals with D-lactic acidosis. These gastrointestinal symptoms are often related to the underlying conditions causing D-lactic acid accumulation.
4. Metabolic Acidosis: Elevated D-lactic acid levels can contribute to metabolic acidosis, an imbalance in the body’s acid-base equilibrium, leading to a decrease in blood pH. This can have systemic effects and affect various organs and bodily functions.
5. Impaired Energy Production: D-lactic acid can interfere with cellular metabolism and energy production, potentially contributing to fatigue and weakness.

Looking up Lactate Value

Clicking on this tab button shows the thousands of metabolites that can be estimated on MP from KEGG data which we can search over.

and we find Lactate (C3H6O3) listed at 27%. IMHO that is low and you want to increase it. The description provided on this is below.

1. Energy Production: Lactate is produced as a result of the breakdown of glucose during anaerobic metabolism when the body’s demand for energy exceeds its oxygen supply. It serves as an alternative fuel source, particularly for muscles and red blood cells, and can be converted back into glucose (gluconeogenesis) in the liver.
2. Exercise and Muscle Function: During intense physical activity, the body produces lactate as muscles work vigorously, leading to temporary increases in blood lactate levels. Contrary to earlier beliefs associating lactate with muscle fatigue and soreness, lactate is not the primary cause of muscle fatigue but is rather utilized as a fuel by muscles and other tissues.
3. Lactate Threshold: The lactate threshold is the exercise intensity at which lactate begins to accumulate in the blood more rapidly than it can be cleared. Athletes often train to improve their lactate threshold, as it correlates with performance and endurance in certain sports.
4. Clinical Implications: Elevated lactate levels in the blood (lactic acidosis) can occur due to various conditions, such as sepsis, shock, hypoxia, liver disease, certain medications, or metabolic disorders. Severe lactic acidosis can lead to symptoms such as rapid breathing, nausea, abdominal pain, and, in severe cases, it can be life-threatening if left untreated.
5. Health Conditions: While lactate plays essential roles in energy metabolism, excessive accumulation due to underlying health conditions or imbalances can lead to health issues. Conditions associated with lactic acidosis require proper medical evaluation and treatment.
6. Diagnostic Tool: Blood lactate levels are sometimes measured in clinical settings to assess tissue oxygenation, especially in emergency and critical care situations, as elevated lactate levels can indicate tissue hypoperfusion and metabolic stress.

This is a follow up to this analysis ME/CFS after trying suggestions from Dr.A.I. from 2 years ago. The goal of MicrobiomePrescription is not to cure any condition — rather to generate suggestions that have a high probability of mitigate a person’s symptoms. Mitigate means reduce severity or eliminate. With some condition, it could result in a technical remission (i.e. no longer matches a diagnostic criteria). The term remission and not cure should be used always — because the microbiome could return to a dark place due to future events or inadequate ongoing care.

Update Story

I’ve been doing MUCH better for the last two years. I feel nowhere near the “normal” levels of energy that a 36 years old man should have and a lot of things are difficult, but I’ve been better and I’m able to work full time as a web developer, remotely. I know live with my significant other, and working + living with someone takes absolutely all of my energy, so I usually have no resources left to meet friends or do extra activities, but the fact of being able to work full time is a huge improvement compared to two years ago. Most of the brain fog has lifted. It comes back on my bad days, but it’s really not as bad as it used to be. 

I feel that my energy levels are going worse these days and it’s getting harder to work full time though. That’s why I’ve done another microbiome analysis, and it seems to be even “worse” than 2 years ago, according to Biomesight’s score. 

I still have trouble digesting things (even though it’s been a bit better the last two years, it has never been “normal” I think) and get diarrhea quite often. I usually have to go to the toilets 5-6 times a day. I’m still very skinny.

I take much less dietary supplements than I used to, but I’m still taking :

• Acetyl L-Carnitine
• Ubiquinole
• R Lipoic Acid
• B12
• Vitamin D
• Nattokinase

I’ve also done another round of “Spezzata”[Licorice] recently, but it definitely makes my blood pressure go up. I also eat a lot of dark chocolate and drink a lot of coffee.

My diet has changed a bit since I’ve started living with my Significant Other about a year ago. I eat a lot more rice than I used to now.

Analysis

The first thing that I noticed was the lab quality is down a lot. Lower quality means less bacteria types (793 dropped to 334) are identify and the estimated costs have greater uncertainty. On the plus side, all measures are the same or are significantly better.

Criteria	Current Sample 2024	Old Sample 2022
Lab Read Quality	2	5.4
Lab Quality Adjustment Percentage	85.9	100
Outside Range from GanzImmun Diagostics	19	19
Outside Range from Lab Teletest	25	25
Outside Range from Medivere	15	15
Outside Range from Metagenomics	9	9
Outside Range from Microba Co-Biome	6	6
Outside Range from MyBioma	8	8
Outside Range from Nirvana/CosmosId	21	21
Outside Range from Thorne (20/80%ile)	327	327
Outside Range from XenoGene	41	41
Outside Lab Range (+/- 1.96SD)	7	10
Outside Box-Plot-Whiskers	43	118
Outside Kaltoft-Moldrup	24	68
Bacteria Reported By Lab	334	793
Bacteria Over 90%ile	0	99
Bacteria Under 10%ile	0	31
Lab: BiomeSight
Pathogens	16	41
Condition Est. Over 90%ile	0	3

Looking at new features added. Note that the drop in number of bacteria reported impacts many of these values)

Measure	2024	2022
“Leaked” from Oral Cavity [LOW is better]	21.1%ile	65.7%ile
General Health Predictors [More is better]	6	17
Jason Hawrelak Ratio	10%ile	14%ile
Butyrate	9%ile	29%ile
Potential Medical Conditions Detected	0	3
Bacteria deemed Unhealthy	0	31
Eubiosis	8%	71.6%ile

The charts show similar patterns but with a group of bacteria dominating (80-90%ile) range

Conclusion: He is better than 2022 in many measures but is worse in a few (especially newer ones).

Let us look at some recent feature additions. First key bacteria — we see improvement we a lot of key bacteria dropping down below the threshold. (see Technical Note: Identifying Key Bacteria to Address for background)

“Leaked” from Oral Cavity is based on this study Oral bacteria relative abundance in faeces increases due to gut microbiota depletion and is linked with patient outcomes, 2024. As with above, we see improvement.

• 2024: 21.1 Percentile.
• 2022: 65.7 Percentile

Going Forward

As usual, I start with “Just give me Suggestions include Symptoms” with the new refactored algorithm (see Algorithm for “Just Give Me Suggestions”). The items were similar but with just a change of order.

First, let us look at what is currently being take. Microbiome changes over time. The highest for non-prescription items is 327 and lowest -516.

• Acetyl L-Carnitine: 152
• Ubiquinole: AKA COq 10, Not on current suggestions
• R Lipoic Acid: Not on current suggestions
• B12: 82
• Vitamin D: -152
• Nattokinase: looking at bacillus subtilis natto -39
• Spezzata [glycyrrhizic acid (licorice)]: -42
• chocolate : 11.5
• coffee/ Trigonelline (found in Coffee): 152
  • Caffeine: 220

None of the above is clearly a bad choice. The worst, vitamin D tend to be a slow acting supplement. This illustrates that doing a retest every 6 months to reset your course to recovery is likely good practice.

Some observations on suggestions:

• 60% of the top 5 items (all antibiotics) have [CFS], i.e. commonly used by ME/CFS specialists.
• Probiotics:
  • bifidobacterium infantis,(probiotics)
  • lactobacillus salivarius (probiotics)
  • lactobacillus reuteri (probiotics)
  • bifidobacterium longum (probiotics)
• Vitamins
  • Vitamin B1,thiamine hydrochloride
  • Vitamin B7, biotin
• Flavonoids (in terms of food — a wide variety of citric fruits)
  • Hesperidin (polyphenol)
  • Naringenin(grapefruit) (Flavonoid)
  • Luteolin (flavonoid)
• Foods
  • sucralose (a zero calorie artificial sweetener) or aspartame (sweetner) Avoid natural sugars
  • whole-grain barley: 272 aka ß-glucan: 140, likely avoid wheat
  • rhubarb
  • No Dairy

AVOID List

• Sugars: stevia, saccharin
• Starches: resistant starch, resistant maltodextrin
• Supplements: sodium butyrate, Tributyrin, zinc, vitamin d, Vitamin B9,folic acid, iron
• Prebiotics: Psyllium (Plantago Ovata Husk), inulin (prebiotic), cellulose (prebiotic), jerusalem artichoke (prebiotic), gum arabic (prebiotic), Xanthan gum, partially hydrolyzed guar gum
• Diet: low-fat diets, low animal protein diet, high beef diet, high saturated milk fat diet, ketogenic diet, high-protein diet. In other words, moderation.

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.

A reader wrote:

Hi Ken – I’m attempting to use MBP. I recall you linked (a long time ago) to a section that showed a list of probiotics useful in colitis, with each probiotic having the studies. How would I arrive to that page?

There is a multiple step/layer approach that I would use. The sequence is below:

#1 Researched Probiotics Available Retail

Go to https://microbiomeprescription.com/library/ProbioticSearch and type in the name of the condition.

You will see the list of probiotics with the ones with the most studies listed first.

Below it are the links to the studies. You should read at least some of them – some may report “no effect”. The list is generated by a data gathering algorithm on the species and the condition and the condition may be mentioned in passing and not directly referenced or tested.

#2 Use Perplexity AI

Go to https://www.perplexity.ai and just ask “What is the most effective probiotic for…”. I use this AI because it provided links to data sources so I can verify the response

A typical response is below

#3 Probiotic Via Published Microbiome Shifts

In this case we are using the MP engine to generate suggestions. It is inferior in reliability to the above methods but is a reasonable fall back. Go to Medical Conditions with Microbiome Shifts from US National Library of Medicine ( https://microbiomeprescription.com/Library/PubMed ) and search for the condition

You can click the PDF download (which report TOP items only) or click Candidates (all items)

Surprise, surprise! #1 and #2 agree with Perplexity!!! vsl#3 is not listed because we do not have strain information for this mixture of probiotics. Remember – these are computed SOLELY from the microbiome shifts without reference to any studies on ulcerative colitis!

#4 Probiotic via Citizen Science

Goto Symptoms associated with conditions reported for Samples https://microbiomeprescription.com/Library/Symptoms Enter the name — in this case it was not found (not enough samples that people have annotated with ulcerative colitis). In that case, you may want to go over to symptoms you have; for example Diarrhea. This data is conditioned on the lab that the contributor was using and layered by taxa level.

I will be adding a suggestions icon to this page shortly, and you can then review those suggestions. Clicking on the bowl, produces suggestions that can be filtered to probiotics.

#1 and #2 above are #1 and #3 with the most studied one show in above!

Clicking on the symptom name takes you to the symptom page listing all of the bacteria

This will then use the expert system to generate suggestions which can be filtered to probiotics

This is ranked not by the number of studies published but by the ones with the greatest estimated impact by the expert system. We see Mutaflor, L. rhamnosus – and many familiar ones in the researched strain list.

Bottom Line

We have 4 ways of selecting probiotics. For the specific question asked, all 4 converge to the same items. In terms of clinical use, we see that the suggestions based solely on bacteria shifts going through the expert system appear to be cross-validated. IMHO, this explicit expert system works better than the typical MD would.

Backstory

I’ve found your work through PR forum and then your website, it’s really interesting reading all that information and feeling so related to the issues.

For the last year I’ve been house bounded and sometimes bed bounded, all coming from ignoring one year of daily sandy-yellowish diarrhea along with a series of chronic sinus infections that one after another left me in a worst health state to finally being isolated fearing further infections.

I’ve been reading and investigating, trying methylation protocols and probiotics. The probiotic I took was fairly simple (bifidobacterium bifidum and lactobacillus acidophilus) but gave me pretty bad reaction which got me thinking about histamine release, one Google search showed me that those strains are not histamine releases but what it does (acidophilus) is increase D-lactic production and what other bacteria could do this? Streptococous, the one which probably caused my chronic sinusitis.

This is how I ended up thinking that I really need to know if I have those kind of bacterial overgrowth in my guts and reading your work thougth that you could have some advice to start learning how to do it.

Analysis

Given that sinus is significant, this study may be worth a read: Oral bacteria relative abundance in faeces increases due to gut microbiota depletion and is linked with patient outcomes, 2024.

I looked at “Leaked” from Oral Cavity and while the count places him at 49%ile, the number of bacteria was much longer than usual — a lot of different bacteria at low levels which suggests a new statistics to add in the next revision.

Going Forward

Since symptoms are entered, I am just using the Just Give Me Suggestions with Symptoms button.

The suggestions are below, trimmed a little

• sucralose
• lauric acid(fatty acid in coconut oil,in palm kernel oil,)
• enterococcus faecium (probiotic)
• garlic (allium sativum)
• momordia charantia(bitter melon, karela, balsam pear, or bitter gourd)
• Tudca – Tauroursodeoxycholic acid , a supplement
• lactobacillus casei (probiotics)
• whole-grain barley
• fruit/legume fibre
• bifidobacterium infantis,(probiotics)
• dates
• grape polyphenols
• naringenin(grapefruit) (Flavonoid)
• Cacao
• rosa rugosa (Rosavin – an adaptogen)
• Hesperidin (polyphenol)
• Nicotine, Nicotine Patch
• galla chinensis (herb)
• Grapefruit seed extract
• lactobacillus gasseri (probiotics)
• thyme (thymol, thyme oil)
• foeniculum vulgare,fennel
• Turmeric
• N-Acetyl Cysteine (NAC),
• Onion

I will create two extracts: one for probiotics and one for teas (i.e. herbs).

Looking at probiotics, we have a good number that would allow easy rotation of probiotics. Two are usually difficult to obtain are removed: lactobacillus kefiri and lactobacillus sakei . Most are available at my usual two preferred sources: Custom Probiotics and Indian Bulk Exporter (Maple Life Sources). See this list for sources not available there. By rotation, I mean 20-50 BCFU daily of one probiotic for 2 weeks and then change to another probiotic.

• enterococcus faecium
• lactobacillus casei [CB,MLS]
• bifidobacterium infantis, [CB,MLS]
• lactobacillus gasseri [CB,MLS]
• lactobacillus jensenii [MS]
• lactobacillus salivarius [CB,MLS]
• pediococcus acidilactic
• bifidobacterium breve [CB,MLS]
• bifidobacterium pseudocatenulatum,
• bifidobacterium longum [CB,MLS]
• bacillus coagulans

While taking herbs as capsules or oils is very viable, herbal teas has the advantage of effecting the oral cavity (and thus sinus) and extends through the entire system.

• thyme
• fennel
• anise
• chamomile
• eugenol (from clove oil, nutmeg, cinnamon, basil,bay leaf.)
• peppermint
• sage
• tulsi
• neem
• oregano
• ginger

Items to avoid or reduce

• Slippery Elm
• wheat bran, rice bran
• xylan (prebiotic)
• inulin (prebiotic)
• arabinogalactan (prebiotic)
• stevia, saccharin
• resistant starch, resistant maltodextrin, slow digestible carbohydrates
• Human milk oligosaccharides (prebiotic, Holigos, Stachyose)
• red wine
• pectin
• l-citrulline (supplement)
• berberine (supplement)
• Pulses
• apples, nuts, banana
• galacto-oligosaccharides (prebiotic)
• low-fat diets, high beef diet, high red meat, animal-based diet, hypocaloric hyperproteic diet
• iron
• Pork
• kefir
• bacillus licheniformis,(probiotics)
• fasting
• galactose (milk sugar)
• propionate
• Guaiacol (polyphenol)

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.

After a good night sleep after doing the video below, I realized the next step in this journey. With hundreds of bacteria in the microbiome the question arises which ones to focus on if the condition is not a known single bacteria condition. I.e. Crohn’s, Asthma vs Tuberculosis, Ulcers.

Recently I had major success is identifying bacteria associated to hundreds of symptoms. This was done by using the percentile ranking of each microbiome sample over the population and then examining the counts of the top and bottom 15%ile (simplified version). These should be equal if there is no relationship of the bacteria to the symptom. The difference allows a Chi2 value and probability to be computed for significance. Comparing the averages perform very poorly for finding equivalent statistical significance.

The result was a list of bacteria where the high in these end 15%ile was associated with symptoms / diagnosis. This allows us to filter out the noise from the significance in a sample. The question arises, should all of these be used or is there a critical limit? The current count is 1,960 taxa-shifts with one or more

To address this issue, I decided to plot the counts.

Applying a log function found a region became a straight line. Two apparent inflection points are suggested. Applying different function kept showing the same inflection points.

Bacteria with high and low associated to Symptoms

There are two species in this list. Both are reported in published clinical studies often.

Bacteria	Rank
Faecalibacterium prausnitzii	species
Dorea formicigenerans	species
Weissella	genus
Faecalibacterium	genus
Acidaminococcaceae	family
Acidaminococcales	order

The Short List of Bacteria

We see many bacteria not usually associated plus two familiar ones. Increases means more are in the 85-100%ile, decrease means more are in the 0-15%ile

Bacteria	Rank	Direction	Count of Associations
Thermodesulfobacteriota	phylum	increases	460
Rhodothermota	phylum	increases	247
Rhodothermia	class	increases	247
Rhodothermales	order	increases	247
Actinomycetota	phylum	decrease	146
Holdemania	genus	increases	135
Faecalibacterium	genus	decrease	133
Coriobacteriaceae	family	decrease	125
Coriobacteriales	order	decrease	120
[Clostridium] thermoalcaliphilum	species	increases	116
Coriobacteriia	class	decrease	115
Lactobacillaceae	family	decrease	114
Bifidobacterium	genus	decrease	113
Sphingobacteriaceae	family	increases	113

Longer List of Bacteria

Bacteria	Rank	Shift	Count
Oscillospiraceae	family	decrease	108
Anaerotruncus colihominis	species	increases	107
Actinomycetes	class	decrease	106
Bacteroides	genus	increases	106
Hathewaya	genus	increases	105
Sharpea azabuensis	species	increases	105
Bacillota	phylum	decrease	105
Sharpea	genus	increases	105
Anaerotruncus	genus	increases	104
Sphingobacteriia	class	increases	104
Sphingobacteriales	order	increases	104
Lactobacillales	order	decrease	101
Ruminococcaceae	family	decrease	101
Erysipelothrix muris	species	increases	100
Erysipelothrix	genus	increases	96
Veillonellaceae	family	increases	94
Bacteroides caccae	species	increases	92
Clostridia	class	decrease	90
Bacteroides fluxus	species	increases	89
Eubacteriales	order	decrease	89
Ethanoligenens	genus	increases	89
Finegoldia	genus	increases	88
Hathewaya histolytica	species	increases	87
Hymenobacter xinjiangensis	species	increases	87
Roseburia faecis	species	decrease	85
Blautia obeum	species	decrease	84
[Clostridium] leptum	species	increases	83
Hymenobacter	genus	increases	82
Negativicutes	class	increases	80
Terrabacteria group	clade	decrease	79
Bifidobacteriaceae	family	decrease	79
Bacilli	class	decrease	78
Bifidobacterium adolescentis	species	decrease	78
Marvinbryantia	genus	increases	77
Phocaeicola vulgatus	species	increases	77
FCB group	clade	increases	76
Odoribacter denticanis	species	increases	75
Mediterraneibacter	genus	increases	74
Faecalibacterium prausnitzii	species	decrease	73
Eggerthella	genus	increases	72
Bifidobacteriales	order	decrease	72
Lachnoclostridium	genus	increases	70
Acidaminococcales	order	increases	70
Odoribacter	genus	increases	70
Acidaminococcaceae	family	increases	70
Blautia schinkii	species	increases	69
Dorea formicigenerans	species	increases	69
Collinsella	genus	decrease	69
Bacteroides stercoris	species	decrease	69
Lactobacillus	genus	decrease	68
Pseudomonadota	phylum	increases	67
Odoribacteraceae	family	increases	67
Peptoniphilaceae	family	increases	67
Fusobacteriaceae	family	decrease	66
Dorea formicigenerans	species	decrease	66
Amedibacillus dolichus	species	increases	65
Amedibacillus	genus	increases	65
Candidatus Glomeribacter	genus	increases	64
Eggerthella lenta	species	increases	63
Finegoldia magna	species	increases	63
Oscillatoria corallinae	species	increases	62
Ruminiclostridium cellobioparum subsp. termitidis	subspecies	decrease	62
Oscillatoria	genus	increases	62
Tissierellales	order	increases	62
Ruminiclostridium cellobioparum	species	decrease	62
Hymenobacteraceae	family	increases	62
Pseudoflavonifractor	genus	increases	61
Mycobacteriales	order	increases	61
Tissierellia	class	increases	60
Lachnoanaerobaculum	genus	decrease	60
Coprococcus	genus	decrease	59
Blautia	genus	increases	59
Collinsella aerofaciens	species	decrease	59
Verrucomicrobiota	phylum	increases	59
Veillonellales	order	increases	58
[Ruminococcus] gnavus	species	increases	58
Selenomonas infelix	species	increases	58
Eubacterium ventriosum	species	decrease	58
Lactonifactor	genus	increases	57
Bacteroides cellulosilyticus	species	increases	57
Enterococcaceae	family	decrease	57
Fusobacterium	genus	decrease	57
Alistipes putredinis	species	increases	57
Sutterella	genus	decrease	56
Anaerotignum lactatifermentans	species	increases	56
Anaerotignum	genus	increases	56
Clostridium akagii	species	increases	56
Burkholderiaceae	family	increases	55
Akkermansiaceae	family	increases	55
Turicibacter	genus	decrease	55
Butyricimonas	genus	increases	55
Segatella copri	species	decrease	55
Mycoplasmoidales	order	increases	55
Turicibacteraceae	family	decrease	55
Turicibacter sanguinis	species	decrease	55
Akkermansia muciniphila	species	increases	54
Sporomusaceae	family	increases	54
Limnobacter	genus	increases	54
Limnobacter litoralis	species	increases	54
Lactobacillus rogosae	species	decrease	54
PVC group	clade	increases	54
Thiocapsa	genus	increases	53
Sphingobacterium bambusae	species	increases	53
Enterobacteriaceae	family	increases	53
Pseudoflavonifractor capillosus	species	increases	53
Blautia hansenii	species	increases	53
Akkermansia	genus	increases	53
Marvinbryantia formatexigens	species	increases	52
Enterococcus	genus	decrease	52
Corynebacteriaceae	family	increases	52
Lachnospira	genus	increases	52
Lachnospira eligens	species	increases	52
Corynebacterium	genus	increases	52
Mycoplasmataceae	family	increases	52
delta/epsilon subdivisions	clade	decrease	52
Bacteroides faecis	species	increases	52
Bacteroides gallinarum	species	increases	52
Veillonella	genus	increases	51
Weissella	genus	increases	51
Dialister invisus	species	increases	51
Blautia hydrogenotrophica	species	increases	51
Lactonifactor longoviformis	species	increases	50
Dorea longicatena	species	decrease	50

Best Test/Lab?

The above is based on percentile and not the typical percentage. The results from Clinical Microbiomics A/S (a.k.a. CosmosId) provides percentile ranking again a regionalized healthy population. In the US, their tests are available retail from Thorne. They will soon be available retail from Precision Biome in the EU.

A walk thru using Microbiome Prescription