Have you ever heard from anyone who felt significantly worse on antibiotics? Since 2020 when I had ebv and iv antibiotics for an infection I can’t tolerate antibiotics like I used to. Low dose doxy 50mg makes me feel very unwell within a few hours, clarithromycin is better tolerated but if I take that I get severe abdominal pain after meals and reduced physical function which only pro and prebiotics fix. If I take a broad spectrum like metronidazol that completely fucks me up (pardon my french!) and I have to get into bed as I cannot stay awake.
There can be multiple causes, the most likely is a Jarisch–Herxheimer reaction a.k.a. “die-off”. (see this article). I have written about these for many years with a few prior posts.
There are other possible causes, for example, something is being feed and more chemicals are being dumped into your system. That is best determines with lab tests.
So to see explore possibilities (I deal with probabilities, not certainty), For your sample go to My Profile. You will see the new link there under Special Reports. Other common possible causes are probiotics that produce d-lactic acid (often causing brain-fog) or histamines.
Enter what causes you to feel worse on the left size, click compute and see which bacteria are likely being lowered.
A friend got this diagnosis from a naturopath examining blood cells using a microscope. Visual inspection of blood lacks the degree of objectivity that I would prefer (AI imaging of the microscope slides is what I would like to see things evolve to). I went to Microbiome Prescription’s Medical Conditions with Microbiome Shifts from US National Library of Medicine and then look at the candidate suggestions for Nonalcoholic Fatty Liver Disease (nafld) Nonalcoholic .
Out of curiosity, I did a few cross validations for the highest to take and highest to avoid. Everything was in agreement. The few suggested items that I checked were shown to have the desired impact on NAFLD.
The purpose of cross validation is to see how well the Artificial Intelligence Logic (and assumptions) are performing.
I decided to do a deeper cross validation because I found that the treatment literature was relatively abundant. REMEMBER the AI only knows the bacteria shifts and nothing about the diagnosis or treatments.
Items to Take
In priority order, the top items with AI Weight of 20 or more
There is a strong bias to publish positive results, hence finding many n/a in the to avoid list is expected. A study show an adverse effect is unlikely to see publication. We see the following ratios:
To Take: 22 Right to 2 Wrong, i.e. 92% correct
To Avoid: 10 Right to 2 Wrong i.e. 83% correct
This suggests that the n/a ones above are likely to be correct.
A reader forwarded his results and ask if they could be uploaded. It was a CSV file which was a good sign. Inspecting the file I noticed two things:
No NCBI Taxonomy numbers were included 🙁
The report gave percentile numbers for every bacteria — a wonderful thing to see.
The reader approached Thorne support about getting the NCBI Taxonomy numbers added — with no success. After a few days of work I ended up with 99.9% success of matching their bacteria names to NCBI Taxonomy numbers. The import worked… but wait! The price is about the same as some 16s tests, but you get MORE DATA and more accurate data! See this study for the difference between 16s and Shotgun
This is whole-genome shotgun metagenomics which is more accurate. It provides percentiles against a much larger sample than I could hope to get. My site is focused on percentiles — so most thing flows nicely – even when there is just one sample!!!
There are items that will not work until we hit 100+ samples from Thorne (i.e. KEGG Percentile Ranking, Pub Med Condition Percentile, etc).
We use Thorne’s PercentilesInsufficient Data To Use these options
We substitute Percentage Match for Percentile in this section (since we are less than 100 samples)
KEGG is based on Percentiles
Bottom Line
I have ordered Thorne for my next test and expect to keep using them if the pricing stays the same. These test costs are driven by technology — which keep dropping cost over time. I recall spending $1000 to get 1 Meg of RAM many decades ago, today for the same amount, I can get 320 GB of memory — that’s 320,000 x more! The same thing is happening with microbiome and DNA testing technologies.
Common approaches to analyzing DNA from a community of microbes, called a microbiome, can yield erroneous results, in large part due to the incomplete databases used to identify microbial DNA sequences.
The process is equivalent to naming a person’s last name from a random DNA sample of a person.
To reduce the uncertainty of microbiome data, the effort in the field must be channeled towards significantly increasing the amount of available genomic information and optimizing the use of this information.
The analogy of “The process is equivalent to naming a person’s last name from a random DNA sample of a person” is a good description of the issue. If you get more people DNA is the database, the odds of correctly identifying the person’s birth last name increases…. naming the bacteria species or strain has the same issue.
For the purposes of Microbiome Prescription, it is not a significant factor because the Artificial Intelligence is based on odds and probability (just like finding the name). For a human, you may identify that it is likely a Norwegian or Dane and thus the last name likely ends with a “sen” with 4.6% odds of being a Jensen (see more here). It is significant if your ideology requires absolute answers.
This post is intended to educate people more on the technical aspects of the microbiome. I am not talking about taking 4 samples from one stool and sending it to 4 different testing company. I am talking about one sample sent to one testing company which then provided their analysis and a FASTQ file. The raw data.
What is a FASTQ file (besides being megabytes big)? It is the DNA (technically the RNA) of the bacteria in the stool. It looks like this (using the 4 letters that DNA has):
The file that I am using as text would be around 16 megabytes. This data comes from a lab machine. The company then processes it through their software to match up sequences to bacteria.
In this post, I am using the FASTQ from uBiome and getting reports on the bacteria from:
ubiome
thryve inside
biomesight
sequentia biotech.
Naively, one would expect almost identical results. What I got is shown in detail below. At a high level we had the following taxa counts reported
ubiome – 253
thryve inside – 632
biomesight – 558
sequentia biotech 366
I did a more technical post on my other blog. From some providers, a taxonomy may be 40% on another 2% or even none… ugly!
Number One Issue: You cannot, repeat cannot, compare a taxonomy report from one lab with another. EVER!
I have 8 uBiome reports and 2 Thryve reports. I can compare the uBiome to each other and the Thryve to each other. I can never mix their direct taxonomy reports !
Number Two Issue: If I wish to compare different lab reports, I MUST obtain the FastQ files from each lab and process them thru the same provider. The FastQ files are the raw data! For me, I prefer to push them through multiple providers which means that the 10 reports suddenly become 40 or 50 different reports in my site.
This means a lot more work for the typical user. It also means that guidance, like that from Jason Hawrelak Criteria for Healthy Gut, would need to be revised to be provider specific!
I have revised my site to show data by specific provider (while keeping the across all provider data still available). A lot of pages to revise and test.
My mom got the AstraZeneca Vaccine last year, after which she didn’t really have any major problems, so later she got her 2nd shot with BionTech/Pfizer. Shortly after she caught Covid. While the course of the disease was very mild, she experienced severe hair loss in the following days, which reverted 6 months later. Also, she started feeling tired fast and could not work anymore (nurse). That was about a year and a half ago.
She developed hypertension after she received the vaccination for COVID
As of now, she still has the same issue with CFS, though it’s gotten better on most days. Some days she gets a crash and doesn’t feel too good. What’s helping her is going outside twice to three times a day for extended walks, and she says when she goes into the pine forest nearby she feels refreshed afterwards.
Her CFS isn’t as severe as my brothers, though it still restricts her from working.\
The Lab used was BiomeSight which ships world wide. An equivalent alternative in the US is Ombre.
Analysis
I am going to do a pro-forma review, i.e. a process that other can follow easily.
My Profile/Health Analysis
Potential Medical Conditions Detected
hypertension (High Blood Pressure 78%ile (12 of 35) prevalence 47%, so likely (and confirmed)
Acne 48%ile (4 of 20) , prevalence 47% — so very unlikely.
Since we have a condition, Long COVID or ME/CFS, we look at:
PubMed data first ( After logging in, Go to https://microbiomeprescription.com/Library/PubMed pick the sample OR see bottom of Changing Microbiome tab)
Going to Medical Conditions with Microbiome Shifts from US National Library of Medicine and sorting by status can be used to look at risks of slipping into additional issues. In this case IBS and SIBO are shown — both are commonly associated with ME/CFS. Coronary artery disease has been associated with COVID (“The risk of heart failure increased by 72%” [2022]). These could be included in building consensus suggestions.
Suggestions
Antibiotics List for MDs produced a list of many antibiotics often prescribed for ME/CFS by some specialist ✅, including:
I strongly favor Dr. Cecile Jadin approach which would be do each month a course (7-10 days) of one of the above and then move on to the next one in the following month. (See Manly Conference February 1999)
Escherichia coli is the top one, which agrees with the Alison Hunter Memorial Foundation presentations in 1998. E.Coli does not get reported in 16s reports and hence tends to be ignored in studies :-(.
Other ones included (in amount of contribution to deficient enzymes):
I explicitly checked against the new list of Bacteria Triggering Coagulation and Micro clots, and they were none at over 75%ile; so coagulation is unlikely to part of the situation. I view coagulation as a potential feedback loop to keep CFS/Long COVID going. The coagulation drops oxygen levels which encourages the growth of bacteria that produces coagulation – a nasty feed back loop.
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.
“The identified microbiome pattern of healthy ageing is characterized by a depletion of core genera found across most humans, primarily Bacteroides. Retaining a high Bacteroides dominance into older age, or having a low gut microbiome uniqueness measure, predicts decreased survival in a 4-year follow-up.” Gut microbiome pattern reflects healthy ageing and predicts survival in humans[2021]
While we have over 4000 samples, most of the samples are from people dealing with health issues. The average number of matches for each age group (when given) is shown below. If your own values is significantly above the number under Matches, you should have some concerns. We do see the number increases around 70.
Lab
Age Range
Matches
OmbreLab
Age: 30-40
5.1
OmbreLab
Age: 40-50
4.8
OmbreLab
Age: 50-60
4.7
OmbreLab
Age: 60-70
5.2
OmbreLab
Age: 70-80
6.7
BiomeSight
Age: 30-40
4.8
BiomeSight
Age: 40-50
4.5
BiomeSight
Age: 50-60
4.6
BiomeSight
Age: 60-70
4.2
BiomeSight
Age: 70-80
3.9
BiomeSight
Age: 80-90
7
I am 70, and decided to look at the last few years of samples. I noticed a blimp with a relapse of ME/CFS which slowly declined with remission.
Sample Date
Matches
Comment
October 20, 2019
5
December 6, 2019
7
ME/CFS Relapse
December 13, 2019
7
February 23, 2020
5
October 29, 2020
6
July 27, 2021
6
September 9, 2021
4
January 24, 2022
4
May 23, 2022
4
September 18, 2022
5
December 1, 2022
5
Using OmbreLab tests
Using BiomeSight processing (which allows my earlier ubiome data to be added). We see the unhealthy spike with ME/CFS
Sample Date
Matches
November 6, 2017
3
March 16, 2018
5
Work Stress
March 19, 2019
7
ME/CFS Flare
April 9, 2019
7
February 23, 2020
5
November 17, 2020
4
September 9, 2021
6
January 24, 2022
4
REMEMBER: Quality of processing of samples can vary greatly. The above should be taken with 0.1 grams of NaCl.
Example of Getting Suggestions
I used Microbiome Prescription site to identify these 4/5 and get suggestions. First, note that different labs detect things differently (See The taxonomy nightmare before Christmas…). The bacteria selections done below are based on the percentile ranking (> 75%ile or < 25%ile) of other lab results from the same lab.
Top Suggestions
What we see is that 5+4 = 8 bacteria of concern — only Enterobacteriaceae was shared between labs.
I then went over to Multiple Samples Tab and looked at the multiple sample Consensus
With the results shown below
The last two are interesting, with the consequence being a shift from chicken to using beef (and with likely smaller portions).
Bottom Line
As shown above, I would recommend getting your FASTQ files processed by both OmbreLab and BiomeSight … a continuing part of The taxonomy nightmare before Christmas… Then do both through this system and getting a Consensus report across samples.
The question of which bacteria may induce coagulation issues and micro clots with Myalgic encephalomyelitis/chronic fatigue syndrome and Long COVID has been an interest for many years (pre-COVID). This week I started digging (again) and this time we got sufficient information to do a sharing post.
Blood coagulation often accompanies bacterial infections and sepsis and is generally accepted as a consequence of immune responses. Though many bacterial species can directly activate individual coagulation factors, they have not been shown to directly initiate the coagulation cascade that precedes clot formation. Here we demonstrated, using microfluidics and surface patterning, that the spatial localization of bacteria substantially affects coagulation of human and mouse blood and plasma. Bacillus cereus and Bacillus anthracis, the anthrax-causing pathogen, directly initiated coagulation of blood in minutes when bacterial cells were clustered.
Paraprevotella had a positive correlation with fibrinogen
Succinatimonas had positive correlations with fibrinogen and homocysteine
Bacillus had positive correlations with fibrinogen and high-sensitivity C-reactive protein
Paraprevotella, Succinatimonas, and Bacillus were also associated with greater plaque volume
Helicobacter pylori, Chlamydia pneumoniae, Mycoplasma pneumoniae, Haemophilus influenzae, Streptococcus pneumoniae, Staphylococcus aureus, Streptococcus pyogenes, Pseudomonas aeruginosa, Klebsiella pneumoniae, Bartonella henselae and Escherichia coli, causing infections may increase the risk of thrombotic complications through platelet activation or may lead to an inflammatory reaction involving the fibrinolytic system. Acinetobacter, Burkholderia pseudomallei [2020]
“The found slight increases in FVIII:C and CRP levels might support the hypothesis that a vancomycin-induced gram-negative shift in the gut microbiome could induce increased systemic inflammation and thereby a procoagulant state.” [2021]
“significantly abundant genera were observed in the coronary thrombus in the patients: Escherichia, 1.25%; Parabacteroides, 0.25%; Christensenella, 0.0%; and Bacteroides, 7.48%. ” [2020]
The artificial intelligence producing these suggestions knows nothing about coagulation, it made these suggestions to solely reduce the bacteria identified above. Bacteria which may cause coagulation.
We would expect more matches for high bacteria levels (defined as > 75%ile) of the bacteria identified above with people with Long COVID and people with ME/CFS. This appears to be shown in the data. The reason that exogene has a very high number is that it reports on all of the candidate bacteria — which is not the case for 16s tests. Second, we see post-COVID people with full recovery having less matches then the combination of samples which includes those that provided no information (and which would likely contain some Long COVID and ME/CFS people)
Condition Reported
Lab
Reported
Not Reported
COVID
BiomeSight
2.44
2.23
Fully Recovered from COVID (No Long Covid)
BiomeSight
2.28
ME/CFS
es-xenogene
6
3.25
SequentiaBiotech
2.5
1.3
OmbreLabs
2.08
1.94
American Gut
5.74
3.10
BiomeSight
2.29
2.27
uBiome
1.54
1.51
Filtered to sufficient samples. Numbers above are based on the number of matches found
The list of bacteria above is known to be incomplete but the above results does suggest at least a partial identification of the bacteria responsible for coagulation and micro clots.
This is based on bacteria identified in Sleep and the Microbiome – Some Notes. Bacteria level shifts through the day and you do not want to feed the bacteria that are associated with sleep issues. This is theoretical lists that ignores the magnitude of shifts.
To Avoid Before Bed
arabinoxylan oligosaccharides (prebiotic)
bacillus subtilis (probiotics)
berberine
bifidobacterium longum (probiotics)
bile (acid/salts)
Burdock Root
Fisetin
ginger
glycine
inulin (prebiotic)
iron
lactobacillus casei (probiotics)
lactobacillus reuteri (probiotics)
lactobacillus rhamnosus gg (probiotics)
omega-3 fatty acids
saccharomyces boulardii (probiotics)
salt (sodium chloride)
Slippery Elm
sodium butyrate
vitamin d
walnuts
wheat
From Social MediaFrom Social Media
Fine to take
These items will have a reducing impact on at least one of the bacteria. Items in bold has the highest impact.
Arbutin (polyphenol)
bacillus amyloliquefaciens (probiotic)
bacillus coagulans (probiotics)
Baking Soda (Sodium Bicarbonate)
bentonite
Caffeine
camelina seed
cannabinoids
chitooligosaccharides (prebiotic)
diosmin,(polyphenol)
extra virgin olive oil
galacto-oligosaccharides (prebiotic)
Hesperidin (polyphenol)
l-glutamine
linseed(flaxseed)
luteolin (flavonoid)
melatonin supplement
N-Acetyl Cysteine (NAC),
pyridoxine hydrochloride (vitamin B6)
quercetin
resveratrol (grape seed/polyphenols/red wine)
sodium stearoyl lactylate
thiamine hydrochloride (vitamin B1)
Vitamin B-12
vitamin b3 (niacin)
vitamin b7 biotin (supplement) (vitamin B7)
Vitamin C (ascorbic acid)
xylan (prebiotic)
So we have melatonin supplement, camelina seed and a glass of red wine to take with some B-vitamins at bed time!
A special edition blog for the sleepless… Many studies are looking at the microbiome with co-morbid conditions — making conclusions difficult.
“Growing evidence suggests bi-directional links between gut microbiota and sleep quality as shared contributors to health.” [2023]
“Contrary to expectations, timed feeding rendered animals more sensitive to stress” [2023] — so eating by the clock and not the light impacts stress negatively.
“In older adults, shorter sleep duration is associated with an increase in pro-inflammatory bacteria whereas increasing sleep quality is positively associated with an increase of beneficial Verrucomicrobia and Lentisphaerae phyla.” [2022]
“several taxa (Lachnospiraceae, Corynebacterium, and Blautia) were negatively correlated with sleep measures” [2017]
“Blautiaand Eubacterium hallii were microbe markers in the sleep-disordered population” [2022]
“Relative abundances of Streptococcus salivarius and Veillonella were independent predictors of sleep disturbances in MHE patients” [2022]
“class Mollicutes in subjects with poor sleep quality were lower than in the healthy individuals. [2022]
“The relative abundance of Sutterella was significantly lower (0.38% vs. 1.25%) and that of Pseudomonas was significantly higher (0.14% vs. 0.08%) in short sleepers than in normal sleepers” [2021]
“men with poor sleep (PSQI >5) tended to have lower alpha-diversity compared to men with normal sleep (Faith’s PD, beta= -0.15; 95% CI:-0.30-0.01, p=0.06). Sleep regularity was significantly associated with robust Aitchison distances (RPCA) and (phylogenetic-RPCA) PRPCA, even after adjusting for site, batch, age, ethnicity, body mass index, diabetes, antidepressant and sleep medication use, and health behaviors”
the top 5 positively associated with sleep regularity were Faecalibacterium prausnitzii G, OEMS01 sp0900199405, Oscillibacter valericigenes, Faecalibacterium prausnitzii A, and Faecalibacterium prausnitzii C.
[Poorer sleep] associated with Ruthenibacterium lactatiformans, Bacteroides uniformis, Alistipes putredinis, and Escherichia dysenteriae
My personal experience is that for most probiotics, taking just before bedtime helps with sleep. I say most — because a few of them will actually cause issues with falling a sleep. If you have single strains probiotics, you may wish to experiment with the impact of individual strains. Take one strain consistently at bed time, with a significant dosage, for a few days to see the impact (if any). One’s that cause wakefulness, may be ones you should take in the morning.
hello I do not want to bother, I have a question in the laboratories of my country, in the microbiota tests they put veillonella as virulent, but in a recent publication of microbiome prescription I saw that it could be a solution, why do the laboratories attribute virulence to it?
My Answer
That is equivalent to saying “Italians are criminals”. Why would someone say that? “Some Italians belong to the Mafia”
Veillonella is a genus of gram-negative, anaerobic bacteria that are commonly found in the human oral cavity, gastrointestinal tract, and respiratory tract. While some strains of Veillonella can cause infections, particularly in individuals with compromised immune systems, the majority of strains are considered to be non-virulent or opportunistic pathogens. Some studies have suggested that Veillonella may play a role in certain disease states, such as periodontal disease, but more research is needed to fully understand the potential pathogenic mechanisms of this genus.
From https://chat.openai.com/chat
For a lab to creditably state that, the lab would need to identify the specific strain. Veillonella is a genus, composed of many species, each species is composed of many strains. In terms of our Italian allergy, Italians come from many regions of Italy (species), within each regions are many families (strains). There may be some of these families that tend to being Mafia, others may tend to be priests (and eventually Popes).
Yin-Yang
My attitude is that Yin and yang is a better way of viewing bacteria. Bacteria are out of balance. Too many poor people results in high crime rates (out of desperation), Too many rich people results in low class mobility (the only people that get ahead are their friends, “old school ties”). The “right balance” for a well functioning society varies by country — for example, Iceland versus Haiti. Similarly, your DNA and diet influences what the right balance should be.
This family’s favorite and most effective probiotic is Mutaflor, an Escherichia coli probiotic. All E.Coli is not bad, trying to eliminate all E.Coli is likely a very dumb choice.
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