FastQ Processing Comparisons

David M. ask me about comparing results from different providers of FastQ to Taxon. I had coded it out and was unhappy with what I saw and did not post about it . I had missed a bug and while the link was there – it would error out. That bug is now fixed, and you may use it..,

Select the ones to compare — it should be the same FastQ file for all. In this case I am processing a uBiome FastQ file (so that is a choice)

Click Compare. What you see may explain my earlier post, The taxonomy nightmare before Christmas… This is the SAME DIGITAL DATA being processed thru 4 different software applications …

MicrobiomeSight did not provide taxons so a text match up was attempted (prone to errors)

Bottom Line

Standards seekers put the human microbiome in their sights, 2019

Child Autism microbiome over time – Part 3

In my last post, End Products and Autism, etc, I looked at the end product shifts seen in autism patients uploaded to my analysis site. In this post, I am going to look at the significant ones over time for this child.

The process is simple, go to compare samples, select the desired ones and click [EndProduct Time Line], as shown below.

http://microbiomeprescription.azurewebsites.net/email/compare

I will do all of those reported in the post above and on the page cited.

Watchout for Normal for Age!

We are dealing with a child, and should first look at the pattern seen for children. We do not have enough samples at the moment to be able to drill down into children with autism (as stated on the page).

Similarly, we cannot drill down further into autism until we get more samples.

A fishing expedition

The end products identified are the most likely involved with autism. More probable – not a certainty. Going thru the many charts below, I noted:

  • Between Feb 14 and April 26, 2019 there was major changes visible on many charts that cascaded onwards.
  • It may have been triggered by an increase in Acetate or Lactic Acid shown on the Feb 14 sample
    • DAO and GABA jumped massively on Apr 26, dropped down but slowly increasing afterwards
    • GABA
  • Formic acid, Thiamine and Urolithins kept increasing after that

April 26th Notes: Diet: up to this date still eating mainly soups and all organic home cooked meals and healthy snacks fruit and nuts. Taking full set of recommended supplements tho experiencing nose bleeds.
Feb 14 Notes: After Sample started probiotic L.reuterei and camel milk. Stools consistency soft, solid. Diet: consisted of vegetable soups and also had introduced celery juice in the mornings.
Addendum ” we stopped for a week because I started seeing more irritability as result. ” resumed.

I would suspect that Lactobacillus Reuterei

From 8 bins and 16 bins

Milestone

The data driving end-products is not as complete as I would like it (if you know of a good source of end product to taxa, please email to me!). I refer to it as experimental because of the lack of solid data. Many of the taxa reported to produce some end products are not reported on by 16s labs.

For this person, we see that Lactobacillus Reuteri appears to have triggered significant changes. “Role of Lactobacillus reuteri in Human Health and Diseases“[2018]. It would account for the increase of Lactic acid and periodic courses may be advantageous. Also with L. Reuteri, “acetate is produced at much higher concentrations 76.” 

The production of formic acid is a little concern. This does not mean you will find high levels in the body; you may find some very fat bacteria that feeds on it and it’s salts ( Formate) .

As a result, I want to identify the bacteria that is causing this. First a Visual:

Then I added a new page,

Clicking and then selecting the End Product
We see what the high producers are.. child and parent (a double count scenario)
We can see that almost every sample is sky high

Going over to Peter D’Adamo Data Punk site, we see that this bacteria inhibits a lot of things:

At this point we have several choices – we could click on Eubacteriaceae or Eubacterium and pick up items to add or remove from the menu. Instead, recall in my Child Autism microbiome over time – Part 2 post, we had a hand picked taxa. I am going to add it to that existing mixture:

Doing it on the already selected taxa
Just click the two, and click Create a custom
Our new collection of bacteria taxa that we wish to modify

We now have similar, but also different suggestions then before. The artificial intelligence engine attempts to find the optimal combination for the above bacteria

Note that we have contrary results for the species lactobacillus rhamnosus (probiotics) versus a specific strain lactobacillus rhamnosus gg (probiotics)

Explicit manipulation of end produces is beyond my comfort level. Formate is water soluble, so this may be a moot issue apart from changing pH. I will leave that speculation to medical professionals.

Bottom Line

This is my first detailed end product analysis connected to a symptom or medical. I ended up writing two more analysis page with the final results being interested. This autism child has one bacteria extremely high and because of using end products we discovered that it would end up with a high amount of formic acid altering the gut and from the literature, also see that it would alter the gut pH — causing more changes of gut bacteria. I have seen another “out of control bacteria (top 2% of values)” in another child with autism (but totally different bacteria) after a different probiotic was started. This may be just two unusual cases, but I thought that it should be mentioned.

We ended up combining several parts of this analysis into one hand picked taxa to adjust and have a good list of changes to consider in consultation with your medical professional.

P.S. One more sample result arrived and was uploaded. The predicted symptoms are matches to earlier ones. I will leave it to the mother to inspect the updated charts shown above.

The microbiome of autistic children is challenging because of several factors:

  • Medical studies (over a dozen) do not replicate each other (see Technical Study on Autism Microbiome)
  • Not many samples to work with using citizen science
  • There is a feeling of “instability”

On the positive side, by this series of post – we can make logical deductions of experiments that may be worthwhile. With regular 16s testing (always the same lab please!!!) you can actually see if something made a difference (for better or worst).

A big KUDO to the mother for keeping detailed daily detail notes and granting permission to use the child’s microbiome results.

Feed Back

I feel I got to keep thanking you for all your observations regarding the data. These give me huge clues in which I can find more bread crumbs in how to better help my daughter.

In you 3rd part of your observations on end products you mentioned that Formic acid was increasing, so from studies that is linked to inflammation in the large colon and increase in bad bacteria.  But I also found an interesting study that indicates the following:

“ This study was conducted to explore the in vitrofermentation characteristics for different ratios of soluble to insolubledietary fiber in pig fecal microbiota. The fermentation substrates consistedof inulin and a non-starch polysaccharide mixture and were divided intofive groups according to different soluble dietary fiber (SDF) to insolubledietary fiber (IDF) ratios (SDF 25, 50, 75, and 100%). With the increasedSDF ratio, the total gas production increased, and the pH in the substratedecreased as the fermentation proceeded. The concentrations of lactic acid,formic acid, and acetic acid increased in the high SDF ratio group, whereasthe concentrations of propionic acid and butyric acid increased in the lowSDF ratio group. The genera Clostridium_sensu_stricto_1, Ruminococca-ceae_NK4A214_group, Christensenellaceae_R-7_group, and Rikenella-ceae_RC9_gut_group were enriched in the high SDF ratio group.Correlation analysis indicated that these differential bacteria had thepotential to degrade polysaccharides. These results revealed that high SDF ratios could stimulate the proliferation of fibrolytic bacteria, which in turn degrade fibers to produce organic acids and monosaccharides. Collectively, these findings add to our   understanding of the mechanisms responsible for interaction the rational use of dietary fiber.”

This is also giving me a clue on the type of food that may be contributing to the increase of Formic acid..  as I explore the type of diet I had changed to e.g. no wheat  I reduced the intake of insoluble fiber, then I furthered explored what level of IDF vs SDF foods I have been giving my daughter.  I’ll be looking at my food logs to see the trend.  

THANK YOU!  As I continue in my search.

End Products and Autism, etc

Many months ago, I extracted information from various sources on what end products/metabolites are produced by various bacteria. My reasoning was simple: the symptom may be due to too much OR too little of some metabolite/chemical, like lactic acid. Lactic acid is produced by many different bacteria. If we try looking for patterns with the end products then the specific bacteria become less important, and the combined results of many taxa become apparent.

Over the last weekend, I attend a conference on Autism and the speakers mentioned finding some metabolites too high or too low. I decided to revisit the end product pages and added some new pages. My focus is autism but the approach in this post can be applied on other matters.

The quick summary page

This page just lists the symptoms (like autism, POTS, FM, ME/CFS) and how many metabolites appear to be statistically significant. I should mention that often the pattern is not autism has the lowest values or highest values, but often land in the high medium range — missing high values and low values.

http://microbiomeprescription.azurewebsites.net/Data/EndProductEureka

Looking at AGE 60-70, you can see a lot of age related changes! Lower vitamin B12 and butyrate, higher hydrogen sulfide

Age: 60-70, http://microbiomeprescription.azurewebsites.net/Data/EndProductExplorer2?includes=192

My original thinking is that by taking select supplements you can bring up (or take down) the levels in the gut. My rationale is simple, end products are used by other bacteria. If you are short on one, it will alter the microbiome balance across many taxa, a cascading effect.

Autism: http://microbiomeprescription.azurewebsites.net/Data/EndProductExplorer2?includes=262

With autism, looking at the numbers above there is a pattern of “not in the middle”. The amounts being produced are too high OR too low often. Some items are in one direction:

  • Formic Acid: Too high

We also have finer resolution available which (a surprise to me) often find more items, as shown below.

When we go to finer levels, we actually get more stronger relationships

For Lactic Acid, there are a number that are sky-high. A similar pattern is also seen with a subset of ME/CFS. Trytophan has the values at the highest and lowest 6%. Etc

Bottom Line

Unlike taxa where diet and supplements modifications are obvious steps, a lot of eurekas here may need physicians to know how to proceed. A few items like low production of Vitamin B12 and some amino acids have over the counter supplements available.

Child Autism microbiome over time – Part 2

In Child Autism microbiome over time – Part 1 , I reviewed the predicted symptoms for each samples and saw a regular pattern. As a result, I wrote some code to cluster the taxa from most common predicted symptoms… in english, identified the bacteria that appears to be causing most of the regular predictions.

To get to this new report, on the samples page, click [Compare Samples to Each Other]

On the next page, select the samples to be included and click [Probable Symptoms Cluster]

The next page does the analysis automatically, showing the common symptoms and then ranking the bacteria matching these symptoms

Just check the ones that you wish to include. My rule of thumb is to go down to 1/2 of the highest value (i.e. 16.5 or higher, since the high is 33). Then create the custom profile. At this point it will evaluate all of the samples and add this hand picked to the best sample. (You may wish to delete other hand picked taxas before doing this — so you can find it!)

The handpicked list is in gold.

You can view the choices if you wish

At this point, we are ready to try suggestions

What happens here is not unexpected. Because we are dealing with a different selection of bacteria, suggestions may contradict, others in agreement with Child Autism microbiome over time – Part 1

There is no easy solution.

  • Items recommended by both or avoid by both are the easy part.
  • When there is disagreement, I usually opt to omit them unless there is a specific reason to include.
  • If it is one one but not the other, I am inclined to go with the suggestion.

Tuning

This is artificial intelligence and that usually mean that it can be tuned or adjusted. Whether it makes the results better or worst may be subjective.

Raising the value reduces the symptoms, reduce the bacteria identified
Lowering, increases the symptoms and the number of taxa

A Second Child

There is another mother with a boy with autism who has also been doing regular samples. To my surprise (and likely my AI’s delight!!!) we came up with similar results for symptoms

Bottom Line

This will likely work with many different conditions. I tried it for myself across all of my samples (in remission of ME/CFS and in relapse) as shown below… Needless to say, the AI did an awesome job!

We do not want to work from a single sample. We want to take regular samples to quiet down random noise in the microbiome and identify the masterminds behind any issues.

Getting Started

If you are new, use Thryve Inside (there is a Gut Club Discount Code ) because it is the most used and thus we have more data on it.

Child Autism microbiome over time – Part 1

A reader granted permission to review their child with autism microbiome over time, especially in light of my recent post Technical Study on Autism Microbiome. It presents an opportunity to better understand the dynamics of the microbiome with autism. I say dynamic, because the microbiome keeps changing — sometimes in minor ways, other times major. It is a moving target. This is the first part of several posts. There is a lot of data and some of it caused me to write new tools to answer some questions that arose. I believe that microbiome has significant impact on the severity of symptoms in autism.

One time microbiome testing is foolishness… you need regular ongoing testing to discover what hangs around and what is a visitor passing thru… What hangs around is what is important… Visitors can often be ignored. The microbiome is very dynamic.

You don’t make a call on who going to win the next election by asking the first person you meet on the bus

Ken Lassesen

Timelines of Key Bacteria Taxa

Presentation of the material

Diversity

I find that Species reported often and be informative. Conventional wisdom is that more is better… There was a dramatic change in early 2019.

“Sample after probiotic L.reuterei and camel milk. Consistency soft solid
Diet: consisted of vegetable soups and also had introduced celery juice in the mornings”

Consensus Taxa

Prior post, Technical Study on Autism Microbiome cites:

The values are opposite – not high but very low.

Blautia being Low

Low values are the norm, often at the very bottom

Bifidobacterium being High (in some Published studies)

Usually low, but with two sudden spikes to high. This is reported low in some published studies and high in other studies. It may a volatile taxa with autism — I have seen major swings in another child with autism of Bifidobacterium.

Lactobacillus being High (in some Published studies)

Almost follows Bifidobacterium in flipping between low and high

Citizen Science Taxa

From most significant downwards..

Erysipelatoclostridium genus / Erysipelotrichia class / Erysipelotrichales order – Low

Clear match of pattern

Veillonella – High

Again agreement, with an increasing over time pattern

Senegalimassilia – High

With recent swings from none to high

Marvinbryantia – Low

Desulfovibrionales (Order) Low. This is reported in 92% of this lab’s sample. 6/11 having none is a low probability event.

Eggerthellales (Order) Low

Intestinimonas – Low

Was low and this year jumped

Anaerotruncus Low

Some random jumps but usually low

Pseudobutyrivibrio Low. This one is only seen 57% of the time in Thryve (which is what was used here) and 98% in uBiome. This distribution is not a very rare/unusual one like some following.

Burkholderiales Unusual!! Low and High (few middle ranges). Clicking the link I see 94% have measurable quantities – for only 1 out of 11 samples to have it is a 1 in 174,000,000,000 chance….

Deltaproteobacteria Low

Very high for a while and then collapse to nothing


Alistipes – Low. Clicking thru I see 85% have measurable quantities. For 7/11 samples having none (and when it does, very low)… suggests it’s absence may be significant.

Agreement

Borderline for Significance

Terrisporobacter Medium Low. Clicking this link I see 75% of samples have measurable amounts. For 10/11 samples to have none suggests some significance to its absence.

Breaks from the pattern

Summary Line #1

The following bacteria are rarely seen at all with this child but is very common in other samples. These are also reported as low across the Autism spectrum from Citizen Science:

The premise that we are working off it that the unusual is contributing to autism.

A good question to ask – Is this familial?

The mother has also done a Thryve sample so comparison was easy

Suggesting that it is unlikely due to DNA. It does suggests that giving the daughter a lot of kisses (especially on hands before meals) may have some benefits.. 😉

Suggestions #1: Dive down on this oddity

I went to Bacteria Symptom Explorer Plus (Autism via Citizen Science is there). And custom picked these 4 bacteria taxa that we want to increase. I then create a [Hand Picked Taxa Suggestion].

http://microbiomeprescription.azurewebsites.net/data/SymptomExplorer?includes=262&sampleId=
Our four taxa – all of these are low

We asked for 30 items, and got less – running with direct citations. It was interesting to see Triphala on the list because it reduces many bacteria and may as a consequence increase these!

Note that certain species of Bacillus and Bifidobacterium are good and others are bad!

I tried various ways of expanding suggestions and found only parents increased the list slightly. ß-glucan + linseed(flaxseed) + high fruit intake may translate to Iron-fortified Oat or Barley porridge with flaxseed and fruit for breakfast. Supper with Oregano, Turmeric with lots of cruciferous vegetables (broccoli cabbage)

Looking back at gut based on Suggestions

We look at the probiotics suggested and levels that this person have of then.

Thrive does not report on this one
Nor on this one
Nor this one
Eureka — we have one reporting
It comes and goes — mostly zero. Taking it makes sense
At the unspecified genus level this is a do not take a generic mixture of bifidobacterium

Predicted Symptoms

Going thru the samples, using 0.6 as the cut off point for predictions. Fatigue may manifest itself as irritability. Every single microbiome sample had autism as #1 predicted symptom.

The ouch!

The mother’s microbiome had a surprise… a weak autism-like profile. Only 12 matches (the daughter ranged from 14-21). The mother when she first emailed gave a “no health issue” description.

” Btw, I looked at the probable symptoms for my own sample and .. [many] were right on specially the neurocognitive ones… but a shocker at the blood type.. is 100%   Although none of the symptoms listed have ever been a concern, so sort of lived with it.. but now I’m so curious to exploring the data more.Thank you again for building this awesome tool!”

– Mother

This weekend I attended a conference with two presentations by Jason Hawrelak on Autism and the Microbiome. He presented his hypothesis that with modern western life, each generation’s microbiome becomes a subset of their parent’s microbiome. As a general concept, I agree if there are no radical changes of lifestyle (inconvenient changes usually). It’s a rational explanation for the increase of autism and other microbiome associated conditions. With this model, the mother was likely on the path towards autism(which was likely delivered to her by her mother) and with an additional iteration subsetting her microbiome… her child was dropped into it.

I believe that it is possible to recover significant amount of the lost microbiome. A simple first step is to spend weekends working on an organic farm as volunteer labor. If the kid eats dirt, or sucks on grass or wheat on this farm… he may be potentially repopulating some of the microbiome. I recall walking with my father (a farmer) and his picking straw and grass for me to suck on (unwashed) — I was getting hay bacillus or grass bacillus, a.k.a. Bacillus subtilis. “Farmer common sense medicine”

Next Installment

Coming next is Suggestions #2, looking at the bacteria that dominant the prediction of symptoms across the many samples, namely

  • Official Diagnosis: Autism
  • Comorbid: Constipation and Explosions (not diarrohea)
  • Official Diagnosis: Mast Cell Dysfunction

With these bacteria

NameRankTimes Cited
Dorea formicigeneransspecies33
Sutterellagenus33
Ruminococcaceaefamily30
Faecalibacteriumgenus27
Peptostreptococcaceaefamily27
Dorea longicatenaspecies26
Erysipelatoclostridiumgenus26
Fusicatenibactergenus24
Clostridialesorder24
Sutterellaceaefamily22

Please remember, I am not a medical professional. I am a professional statistician, artificial intelligence engineer and software developer (Microsoft, Amazon, Starbucks etc). I extracted “facts” from medical literature and use these facts to drive a fuzzy logic inference engine (commonly known as Artificial Intelligence).

The intent is to explore logical possibilities that may warrant future studies by medical professionals using statistics.