I had a chat with a work colleague this week, his wife like mine, has suffered from Transient Ischemic Attack induced by stress. This post explores what we know from medical literature about these two things.

An excellent starting point is an article release yesterday: How stressed-out gut bacteria may trigger autoimmune response, Neuroscience News, May 14, 2019.

Bacteria Shifts Seen with Stress

At the genus and species levels, significant enrichment in the
Social defeat [stressed – SD] group feces included Oscillospira, Ruminococcus (FDR = 0.003), and Dehalobacterium (P value = 0.028) (Firmicutes, 2- to 3-fold), Mucispirillum schaedleri (FDR = 0.004) (Deferribacteres, ∼3-fold), and Bilophila (FDR = 0.0004) (Proteobacteria, ∼6-fold) ….
fourteen days after the last exposure of the mice to the aggressor, the structure of the SD-associated bacterial community nearly returned to homeostasis without any significant change 

Genera/species that were significantly enriched in at least one of the experiments included Adlercreutzia (P value = 0.0259; Actinobacteria), Brevundimonas diminuta (P value = 0.044; Alphaproteobacteria; an opportunistic pathogen in immunocompromised hosts [32]), and Helicobacter (P value = 0.022; Epsilonproteobacteria; highly prevalent pathobiont that can lead to gastritis, peptic ulcer disease, and possibly autoimmune diseases [33]), whereas genera/species that were relatively less abundant in SD group MLNs included Sutterella (P value = 0.0163; Betaproteobacteria; reduced in the gut of human patients with MS) and Prevotella (P value = 0.010; 

Social-Stress-Responsive Microbiota Induces Stimulation of Self-Reactive Effector T Helper Cells , 2019

Discussion

We show that an environmental trigger such as social stress affects the bacterial composition and transcriptional patterns in a way that enforces an immune response with potential deleterious consequences to self-tolerance. This might be a hit-and-run effect since although the gut microbial community recovered after the cessation of the stress, the microbial alterations and the immune response in the MLNs persisted, highlighting the consequences of an early stress-inducible disturbance on the homeostasis later in life. In that aspect, many of the stress-responsive bacteria that we found are known to be associated with autoimmunity and other diseases.

The stress-associated virulent phenotype can explain, for example, how under healthy conditions, the relative abundance of Proteobacteria in the human gut can transiently increase from 2.5% to 45% without clinical signs, whereas under certain undefined circumstances, they do trigger inflammatory responses (55–57). 

Social-Stress-Responsive Microbiota Induces Stimulation of Self-Reactive Effector T Helper Cells , 2019

Simple translation, stress alters the microbiome is a way that persists and potentially leaves the person stress intolerant (see this post for the list of medical conditions that are recognized as being stress intolerant).

TIA Microbiome

• “Stroke and transient ischemic attack patients had more opportunistic pathogens, such as Enterobacter, Megasphaera, Oscillibacter, and Desulfovibrio, and fewer commensal or beneficial genera including Bacteroides, Prevotella, and Faecalibacterium. This dysbiosis was correlated with the severity of the disease.”  [2015]
  • Note: higher Oscillibacter and lower Prevotella is seen with stress as reported above.
• “a decreased amount of Roseburia, Bacteroides, Faecalibacterium prausnitzii and increased proportion of Enterobacteriaceae, Bifidobacteriaceae, and Clostridium difficile has been detected in gut samples of stroke patients, as compared to healthy volunteers, intensive care patients, patients with active ulcerative colitis or with irritable bowel syndrome [2012].  “

Bottom Line

The relationship seems self evident from the literature. The question arises, what can be done when under stress? Using the microbiome prescription site at the genus level, we can enter the above shifts and see what is suggested. Note: that if stress cause a condition, then there may be significant shifts as a response.

Increase the following:

Item

lactobacillus rhamnosus gg (probiotics)

lactobacillus casei (probiotics)

inulin (prebiotic)

Ferric citrate

galacto-oligosaccharides (prebiotic)

arabinoxylan oligosaccharides (prebiotic)

bifidobacterium animalis subsp. lactis (probiotics)

cellulose (prebiotic)

oligofructose (prebiotic)

proline (amino acid)

propionate

lactobacillus salivarius (probiotics)

l-citrulline

l-glutamine

mannooligosaccharide (prebiotic)

lactobacillus gasseri (probiotics)

sialyllactose (oligosaccharide ) (prebiotic)

vitamin d

Avoid the following

On the other side, we should avoid the following. Note that here we see some probiotics should be taken and others avoided. Probiotics are not a universal cure-all!

zinc oxide

melatonin supplement

vitamin b7 biotin (supplement) (vitamin B7)

thiamine hydrochloride (vitamin B1)

retinoic acid (prescription)

lactobacillus kefiri (probiotics)

lactobacillus plantarum (probiotics)

pyridoxine hydrochloride (vitamin B6)

chicory (prebiotic)

Cyanocobalamin (Vitamin B12)

folic acid (prescription)

fructo-oligosaccharides (prebiotic)

polymannuronic acid

bifidobacterium longum (probiotics)

saccharomyces boulardii (probiotics)

resistant starch

ß-glucan

vitamin b3 (niacin)

resistant starch type 4

saccharomyces cerevisiae (probiotics)

catechol

Bifidobacterium bifidum (probiotic)

epicatechin

clostridium butyricum (probiotics)

(+)-catechin

jerusalem artichoke (prebiotic)

lactobacillus acidophilus (probiotics)

lactobacillus brevis (probiotics)

Prescript Assist (Original Formula)

lactobacillus fermentum (probiotics)

pyruvate

lactobacillus reuteri (probiotics)

mastic gum (prebiotic)

I have added a new page today that shows the relative production of various vitamins and a few metabolites compared to a healthy population. It is linked to from the samples page.

The regular suggestions pages may list these vitamins because it is known that they will impact other bacteria that we wish to change. There is incomplete knowledge.

This new page computes for known producers, the amount that is likely being produced and compare it to those who declared themselves healthy in the uploads.

Another person’s result

There is a lot of uncertainty in modifying an ill microbiome. This starts with selecting the bacteria you want to change, see this post Steeing the species that may need correction to whether something actually modifies a bacteria without causing undesirable side-effects. You cannot be blinkered to a single bacteria because there are a large number of interactions between different bacteria (often across orders)

The Advance Suggestions page allows you to refine how suggestions are generated and what you are willing to do to modify your microbiome. For example, some people may not wish to do antibiotics (or have MDs that will not prescribe); others may be vegans.

After selecting which 16s Sample to use, you need to pick which way you want your bacteria to be selected as explained in Seeing the species that may need correction.

The next item determines how fine you want the suggestions to be. Let me explain, some suggestions are based on reports of a suggestion impact on a Family or an Order as a reporting unit. If you go to a lower level, you will get less suggestions and they will be more specific to specific bacteria. It’s a trade-off. If you get no suggestion, try moving to a higher level.

The next step is whether you want to include literature reports that a specific bacteria was significant for a specific condition. If you have a condition, then this will increase the odds of the right bacteria being picked. The number of bacteria will likely decrease, and number of suggestions too. There is a long list of conditions:

The next is a list of categories of suggestions that you can filter to. Everything is checked by default. Uncheck the items that you are not interested in.

The last choices limit the items displayed to the best and worst suggestions. In some situation, more than a hundred items were reported with the old process. You can still see all if you want… but this is intended to just shown the best.

Last, when you click, the report will be shown in a NEW WINDOW OR TAB in your browser. This allows you to compare different combinations against each other.

Some sample reports are below:

You can also see how suggestions changes between sample. Once you have a good set of filters, just change the sample and you will see what the older sample would produce.

This ubiome sample was done a week after my last posting. Some interesting things happened during the week:

Changes

• I stopped taking 100-150 BCFU per day (because Lactobacillus et al ) were not at the top of suggestions
• Changed probiotics to Bacillus Coagulans (Digestive Advantages) instead of Bacillus Clausii (Enterogermina)
• Stopped supplementing with Potassium Citrate, Folate and Berbine

Consequences

• Found myself becoming quickly fatigue physically
• Fatigue accompanied with overheating feeling.
• Stools became very burning with frequency increasing every day
• Tested a vial of Bacillus Clausii and could literally feel things becoming better
• Leg cramps, sore muscles across the body

Response

After getting the sample for ubiome, returned to 100+ BCFU of lactobacillus et al probiotics taken with organic yogurt. Stool burning and frequency declined within 12 hours.

When I re-introduced Potassium Citrate, the leg cramps and sore muscles disappeared. I seem to be resetting to where I was 10 days ago.

I wanted to get the sample to get some insight on what went wrong.

Changes

Drill down into specifics

Looking at the raw data for this sample

• Lactobacillus paracasei is at 29/ /1000000
• Lactobacillus casei is at 29/1000000

For prior sample:

• Bifidobacterium animalis 33/1000000
• Bifidobacterium longum 373/1000000
• Lactobacillus curvatus 113/1000000
• Lactobacillus casei 33/1000000

First sample after flare:

• Lactobacillus: 162/1000000 with no species identified
• No Bifidobacterium

Prior to flare

• Lactobacillus: none
• Bifidobacterium 3356/1000000
  • Bifidobacterium bifidum 36/1000000
  • Bifidobacterium animalis 434/1000000
  • Bifidobacterium longum 2885/1000000

It looks like the B.longum and B.animalis were making a comeback after the flare eliminated them with approximately the same ratio. It does hint that
Bifidobacterium animalis and Bifidobacterium longum probiotics are desired to assist.

Unchanged

Change of Suggestions

The new Advance Suggestions makes it easy to compare suggestion between samples. For you current sample, tune the suggestions appropriately. Then just select another sample and see the results. Comparing this (downhill) with the prior sample (uphill), I saw some interesting flips:

• Folate (B9) flipped from avoid to take
• Berbine flipped from avoid to take
• Resveratol (grape seed extract) flipped from avoid to take

This causes me to be careful when something flips from take to avoid when things are improving. The suggestions are just that suggestions (based on a healthy microbiome data). It also indicates that some microbiome populations had significantly altered.

Bottom Line

By symptoms, I knew that I had lost ground with the modifications that I made; this appears to be confirmed by the results. I am restoring the above three to my supplements and then waiting a week before doing the next uBiome sample. I have been doing seed probiotics for a week now, and I am curious if this human source probiotics has any persistence.

A new rule is suggested

If things are improving and a new test’s suggestion says stop on what the last test suggestion says take. — Ignore it.

Some readers have requested that I show the list of bacteria that were selected to make suggestions from. I have done some refactoring and they are now available from three different ways of selecting bacteria that are available on the site now. Reports go down to the strain in some cases.

Choices for Determining What you wish to change

Once you have logged on, if you select Advanced Suggestions

You will go to the custom suggestions page. On this page, you will see your samples and links for Bacteria Selection choices.

There are multiple paths available for determining what could be wrong, and thus what you may wish to modify. Click on the above high lighted link will show you the actual bacteria picked from each of these methods. A short summary of each is below:

• Bacteria that has an association with symptoms that you have and you are an exact match. This will be the smallest list — but it is the most certain of being right
• Bacteria whose population are outliers (that is far away from the expected patterns). This is the medium size list — it is uncertain if they are significant
• Bacteria above or below normal ranges. This is the simplest to understand and may be most leading. The typical 16S report has 500 to 1500 bacteria listed. Assuming the normal range is the middle 90% (5% high and 5% low), we would get 50 to 150 bacteria listed here by random chance.

I did some counts on different samples, which confirms the counts from each method.

Note: The symptom and outlier filter is dynamic. As more data is added, their ability to detect improves. For symptoms, there must be 16 people people reporting the same symptom before we will do detection of association.

In Summary

You can try all three methods, and experiment. You really want to get the smallest list of bacteria (because in figuring out suggestions, the more bacteria you include, the more complex it gets!).

For myself, I did suggestions from each and found a few items appeared in common with all of them. Those items are definitely on my list (“Almonds in the morning, Almonds in the Evening, Almonds at supper time”) sung to the tune below..

https://www.youtube.com/watch?v=bRvEHn6fKWE